Overview

Brought to you by YData

Dataset statistics

Number of variables133
Number of observations45975
Missing cells0
Missing cells (%)0.0%
Total size in memory110.5 MiB
Average record size in memory2.5 KiB

Variable types

Text23
Numeric110

Alerts

pl_insollim has constant value "0.0" Constant
pl_controv_flag is highly skewed (γ1 = 24.53518181) Skewed
planet_period_x is highly skewed (γ1 = 214.0473503) Skewed
pl_orbpererr1 is highly skewed (γ1 = 214.3710701) Skewed
pl_orbpererr2 is highly skewed (γ1 = -212.9770167) Skewed
pl_orbperlim is highly skewed (γ1 = -32.72207607) Skewed
semi_major_axis_x is highly skewed (γ1 = 109.3432131) Skewed
pl_orbsmaxerr1 is highly skewed (γ1 = 212.7638375) Skewed
pl_orbsmaxerr2 is highly skewed (γ1 = -175.7084374) Skewed
pl_orbsmaxlim is highly skewed (γ1 = -123.7861056) Skewed
planet_radius_x is highly skewed (γ1 = 60.95451404) Skewed
pl_radeerr1 is highly skewed (γ1 = 125.1414213) Skewed
pl_radeerr2 is highly skewed (γ1 = -107.738839) Skewed
pl_radelim is highly skewed (γ1 = -58.34127022) Skewed
pl_radj is highly skewed (γ1 = 60.95437607) Skewed
pl_radjerr1 is highly skewed (γ1 = 125.14125) Skewed
pl_radjerr2 is highly skewed (γ1 = -107.7392565) Skewed
pl_radjlim is highly skewed (γ1 = -58.34127022) Skewed
pl_bmasseerr1 is highly skewed (γ1 = 40.93112913) Skewed
pl_bmasseerr2 is highly skewed (γ1 = -62.18485982) Skewed
pl_bmassjerr1 is highly skewed (γ1 = 40.91887394) Skewed
pl_bmassjerr2 is highly skewed (γ1 = -62.20276697) Skewed
pl_insol is highly skewed (γ1 = 38.57508531) Skewed
pl_insolerr1 is highly skewed (γ1 = 41.58030544) Skewed
pl_insolerr2 is highly skewed (γ1 = -52.95627662) Skewed
pl_eqtlim is highly skewed (γ1 = 123.7861056) Skewed
st_tefferr1 is highly skewed (γ1 = 38.07171266) Skewed
st_tefferr2 is highly skewed (γ1 = -35.71018426) Skewed
st_tefflim is highly skewed (γ1 = 214.4178164) Skewed
star_radius_x is highly skewed (γ1 = 28.37729697) Skewed
st_raderr1 is highly skewed (γ1 = 100.4102872) Skewed
st_raderr2 is highly skewed (γ1 = -93.17670228) Skewed
st_radlim is highly skewed (γ1 = 151.611345) Skewed
st_masserr1 is highly skewed (γ1 = 182.7964386) Skewed
st_masserr2 is highly skewed (γ1 = -184.6952829) Skewed
st_metlim is highly skewed (γ1 = -56.83662986) Skewed
st_logglim is highly skewed (γ1 = -56.83662986) Skewed
sy_vmagerr2 is highly skewed (γ1 = -34.85153344) Skewed
sy_kmagerr1 is highly skewed (γ1 = 47.81472403) Skewed
sy_kmagerr2 is highly skewed (γ1 = -52.50056348) Skewed
sy_gaiamagerr1 is highly skewed (γ1 = 22.74225641) Skewed
sy_gaiamagerr2 is highly skewed (γ1 = -22.74225641) Skewed
radius_error_min is highly skewed (γ1 = 192.915668) Skewed
radius_error_max is highly skewed (γ1 = 192.915668) Skewed
planet_period_y is highly skewed (γ1 = 125.1672019) Skewed
orbital_period_error_min is highly skewed (γ1 = 214.4178164) Skewed
orbital_period_error_max is highly skewed (γ1 = 214.4178164) Skewed
semi_major_axis_y is highly skewed (γ1 = 52.98021406) Skewed
star_metallicity_error_min is highly skewed (γ1 = 214.4151264) Skewed
star_metallicity_error_max is highly skewed (γ1 = 214.4151264) Skewed
star_mass_error_min is highly skewed (γ1 = 32.8201421) Skewed
star_mass_error_max is highly skewed (γ1 = 32.8201421) Skewed
star_radius_y is highly skewed (γ1 = 32.79883133) Skewed
star_radius_error_min is highly skewed (γ1 = 42.86649361) Skewed
star_radius_error_max is highly skewed (γ1 = 42.86649361) Skewed
star_teff_error_min is highly skewed (γ1 = 52.07185453) Skewed
star_teff_error_max is highly skewed (γ1 = 52.07185453) Skewed
star_radius is highly skewed (γ1 = 30.83513657) Skewed
planet_period is highly skewed (γ1 = 213.4424967) Skewed
semi_major_axis is highly skewed (γ1 = 136.2717307) Skewed
default_flag has 40156 (87.3%) zeros Zeros
pl_controv_flag has 45899 (99.8%) zeros Zeros
pl_orbperlim has 45961 (> 99.9%) zeros Zeros
pl_orbsmaxlim has 45972 (> 99.9%) zeros Zeros
pl_radelim has 45969 (> 99.9%) zeros Zeros
pl_radjlim has 45969 (> 99.9%) zeros Zeros
pl_bmasselim has 45724 (99.5%) zeros Zeros
pl_bmassjlim has 45724 (99.5%) zeros Zeros
pl_orbeccen has 41874 (91.1%) zeros Zeros
pl_orbeccenlim has 45376 (98.7%) zeros Zeros
pl_insollim has 45975 (100.0%) zeros Zeros
pl_eqtlim has 45972 (> 99.9%) zeros Zeros
ttv_flag has 41824 (91.0%) zeros Zeros
st_tefflim has 45974 (> 99.9%) zeros Zeros
st_radlim has 45973 (> 99.9%) zeros Zeros
st_masslim has 45965 (> 99.9%) zeros Zeros
st_met has 825 (1.8%) zeros Zeros
st_metlim has 45967 (> 99.9%) zeros Zeros
st_logglim has 45967 (> 99.9%) zeros Zeros
star_metallicity_x has 1063 (2.3%) zeros Zeros
star_metallicity_y has 25176 (54.8%) zeros Zeros
is_transiting has 2296 (5.0%) zeros Zeros

Reproduction

Analysis started2025-02-18 19:19:47.950749
Analysis finished2025-02-18 19:19:50.254832
Duration2.3 seconds
Software versionydata-profiling vv4.12.2
Download configurationconfig.json

Variables

Distinct12763
Distinct (%)27.8%
Missing0
Missing (%)0.0%
Memory size3.0 MiB
2025-02-19T00:19:50.391593image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length31
Median length29
Mean length11.62897227
Min length4

Characters and Unicode

Total characters534642
Distinct characters73
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7592 ?
Unique (%)16.5%

Sample

1st row109 Psc b
2nd row11 Com Ab
3rd row11 Com b
4th row11 Com b
5th row11 Com b
ValueCountFrequency (%)
b 32364
33.3%
c 7729
 
8.0%
d 2790
 
2.9%
hd 2518
 
2.6%
e 978
 
1.0%
ab 581
 
0.6%
gj 432
 
0.4%
f 303
 
0.3%
2mass 291
 
0.3%
a 238
 
0.2%
Other values (9383) 48865
50.3%
2025-02-19T00:19:50.679585image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 58583
 
11.0%
51121
 
9.6%
- 43544
 
8.1%
K 35397
 
6.6%
b 33032
 
6.2%
1 31776
 
5.9%
r 29050
 
5.4%
p 28746
 
5.4%
l 28718
 
5.4%
2 22156
 
4.1%
Other values (63) 172519
32.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 534642
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 58583
 
11.0%
51121
 
9.6%
- 43544
 
8.1%
K 35397
 
6.6%
b 33032
 
6.2%
1 31776
 
5.9%
r 29050
 
5.4%
p 28746
 
5.4%
l 28718
 
5.4%
2 22156
 
4.1%
Other values (63) 172519
32.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 534642
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 58583
 
11.0%
51121
 
9.6%
- 43544
 
8.1%
K 35397
 
6.6%
b 33032
 
6.2%
1 31776
 
5.9%
r 29050
 
5.4%
p 28746
 
5.4%
l 28718
 
5.4%
2 22156
 
4.1%
Other values (63) 172519
32.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 534642
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 58583
 
11.0%
51121
 
9.6%
- 43544
 
8.1%
K 35397
 
6.6%
b 33032
 
6.2%
1 31776
 
5.9%
r 29050
 
5.4%
p 28746
 
5.4%
l 28718
 
5.4%
2 22156
 
4.1%
Other values (63) 172519
32.3%
Distinct9056
Distinct (%)19.7%
Missing0
Missing (%)0.0%
Memory size2.9 MiB
2025-02-19T00:19:50.840981image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length29
Median length27
Mean length9.540402393
Min length3

Characters and Unicode

Total characters438620
Distinct characters74
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4241 ?
Unique (%)9.2%

Sample

1st row109 Psc
2nd row11 Com A
3rd row11 Com
4th row11 Com
5th row11 Com
ValueCountFrequency (%)
hd 2526
 
4.8%
a 982
 
1.9%
unkown 780
 
1.5%
gj 439
 
0.8%
hip 223
 
0.4%
epic 173
 
0.3%
2mass 108
 
0.2%
kepler-11 103
 
0.2%
kic 92
 
0.2%
ab 91
 
0.2%
Other values (8683) 46602
89.4%
2025-02-19T00:19:51.019962image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 57515
13.1%
- 43010
 
9.8%
K 35349
 
8.1%
1 30783
 
7.0%
r 28968
 
6.6%
p 28705
 
6.5%
l 28697
 
6.5%
2 21227
 
4.8%
3 16180
 
3.7%
0 14216
 
3.2%
Other values (64) 133970
30.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 438620
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 57515
13.1%
- 43010
 
9.8%
K 35349
 
8.1%
1 30783
 
7.0%
r 28968
 
6.6%
p 28705
 
6.5%
l 28697
 
6.5%
2 21227
 
4.8%
3 16180
 
3.7%
0 14216
 
3.2%
Other values (64) 133970
30.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 438620
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 57515
13.1%
- 43010
 
9.8%
K 35349
 
8.1%
1 30783
 
7.0%
r 28968
 
6.6%
p 28705
 
6.5%
l 28697
 
6.5%
2 21227
 
4.8%
3 16180
 
3.7%
0 14216
 
3.2%
Other values (64) 133970
30.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 438620
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 57515
13.1%
- 43010
 
9.8%
K 35349
 
8.1%
1 30783
 
7.0%
r 28968
 
6.6%
p 28705
 
6.5%
l 28697
 
6.5%
2 21227
 
4.8%
3 16180
 
3.7%
0 14216
 
3.2%
Other values (64) 133970
30.5%

default_flag
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1265687874
Minimum0
Maximum1
Zeros40156
Zeros (%)87.3%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:19:51.054455image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3324929083
Coefficient of variation (CV)2.626973957
Kurtosis3.046213704
Mean0.1265687874
Median Absolute Deviation (MAD)0
Skewness2.246348412
Sum5819
Variance0.110551534
MonotonicityNot monotonic
2025-02-19T00:19:51.092118image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 40156
87.3%
1 5819
 
12.7%
ValueCountFrequency (%)
0 40156
87.3%
1 5819
 
12.7%
ValueCountFrequency (%)
1 5819
 
12.7%
0 40156
87.3%

sy_snum
Real number (ℝ)

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.070255574
Minimum1
Maximum4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:19:51.129371image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile2
Maximum4
Range3
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2828871011
Coefficient of variation (CV)0.2643173351
Kurtosis19.8748575
Mean1.070255574
Median Absolute Deviation (MAD)0
Skewness4.314937524
Sum49205
Variance0.08002511195
MonotonicityNot monotonic
2025-02-19T00:19:51.181244image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=4)
ValueCountFrequency (%)
1 43079
93.7%
2 2566
 
5.6%
3 326
 
0.7%
4 4
 
< 0.1%
ValueCountFrequency (%)
1 43079
93.7%
2 2566
 
5.6%
3 326
 
0.7%
4 4
 
< 0.1%
ValueCountFrequency (%)
4 4
 
< 0.1%
3 326
 
0.7%
2 2566
 
5.6%
1 43079
93.7%

sy_pnum
Real number (ℝ)

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.744143556
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:19:51.228837image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile4
Maximum8
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.153708272
Coefficient of variation (CV)0.6614755237
Kurtosis3.078562512
Mean1.744143556
Median Absolute Deviation (MAD)0
Skewness1.757363085
Sum80187
Variance1.331042777
MonotonicityNot monotonic
2025-02-19T00:19:51.260576image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 27912
60.7%
2 8674
 
18.9%
3 4986
 
10.8%
4 2732
 
5.9%
5 1176
 
2.6%
6 381
 
0.8%
8 77
 
0.2%
7 37
 
0.1%
ValueCountFrequency (%)
1 27912
60.7%
2 8674
 
18.9%
3 4986
 
10.8%
4 2732
 
5.9%
5 1176
 
2.6%
ValueCountFrequency (%)
8 77
 
0.2%
7 37
 
0.1%
6 381
 
0.8%
5 1176
2.6%
4 2732
5.9%
Distinct12
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.8 MiB
2025-02-19T00:19:51.352259image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length29
Median length7
Mean length7.60069603
Min length7

Characters and Unicode

Total characters349442
Distinct characters33
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowunknown
2nd rowunknown
3rd rowRadial Velocity
4th rowRadial Velocity
5th rowRadial Velocity
ValueCountFrequency (%)
transit 34574
70.6%
unknown 7966
 
16.3%
radial 2579
 
5.3%
velocity 2579
 
5.3%
microlensing 644
 
1.3%
timing 191
 
0.4%
variations 178
 
0.4%
imaging 148
 
0.3%
eclipse 24
 
< 0.1%
orbital 21
 
< 0.1%
Other values (7) 62
 
0.1%
2025-02-19T00:19:51.435627image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 60322
17.3%
i 41998
12.0%
a 40294
11.5%
t 37403
10.7%
s 35482
10.2%
r 35457
10.1%
T 34765
9.9%
o 11414
 
3.3%
u 8002
 
2.3%
k 7967
 
2.3%
Other values (23) 36338
10.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 349442
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 60322
17.3%
i 41998
12.0%
a 40294
11.5%
t 37403
10.7%
s 35482
10.2%
r 35457
10.1%
T 34765
9.9%
o 11414
 
3.3%
u 8002
 
2.3%
k 7967
 
2.3%
Other values (23) 36338
10.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 349442
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 60322
17.3%
i 41998
12.0%
a 40294
11.5%
t 37403
10.7%
s 35482
10.2%
r 35457
10.1%
T 34765
9.9%
o 11414
 
3.3%
u 8002
 
2.3%
k 7967
 
2.3%
Other values (23) 36338
10.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 349442
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 60322
17.3%
i 41998
12.0%
a 40294
11.5%
t 37403
10.7%
s 35482
10.2%
r 35457
10.1%
T 34765
9.9%
o 11414
 
3.3%
u 8002
 
2.3%
k 7967
 
2.3%
Other values (23) 36338
10.4%

discovery_year
Real number (ℝ)

Distinct42
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2015.40609
Minimum1781
Maximum2026
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:19:51.483295image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1781
5-th percentile2008
Q12014
median2016
Q32016
95-th percentile2022
Maximum2026
Range245
Interquartile range (IQR)2

Descriptive statistics

Standard deviation4.310450835
Coefficient of variation (CV)0.002138750526
Kurtosis247.866221
Mean2015.40609
Median Absolute Deviation (MAD)2
Skewness-5.803550888
Sum92658295
Variance18.5799864
MonotonicityNot monotonic
2025-02-19T00:19:51.531043image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
2016 17381
37.8%
2014 9879
21.5%
2021 3010
 
6.5%
2012 1328
 
2.9%
2011 1301
 
2.8%
2013 1253
 
2.7%
2023 1189
 
2.6%
2018 1153
 
2.5%
2015 1100
 
2.4%
2022 1063
 
2.3%
Other values (32) 7318
15.9%
ValueCountFrequency (%)
1781 1
 
< 0.1%
1846 1
 
< 0.1%
1930 1
 
< 0.1%
1988 3
< 0.1%
1989 1
 
< 0.1%
ValueCountFrequency (%)
2026 1
 
< 0.1%
2025 24
 
0.1%
2024 789
1.7%
2023 1189
2.6%
2022 1063
2.3%
Distinct72
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size2.9 MiB
2025-02-19T00:19:51.629747image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length46
Median length6
Mean length8.462838499
Min length2

Characters and Unicode

Total characters389079
Distinct characters57
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)< 0.1%

Sample

1st rowunknown
2nd rowunknown
3rd rowXinglong Station
4th rowXinglong Station
5th rowXinglong Station
ValueCountFrequency (%)
kepler 28217
48.8%
unknown 7966
 
13.8%
observatory 2087
 
3.6%
k2 2015
 
3.5%
survey 1605
 
2.8%
satellite 1585
 
2.7%
exoplanet 1562
 
2.7%
transiting 1562
 
2.7%
tess 1562
 
2.7%
superwasp 963
 
1.7%
Other values (125) 8725
 
15.1%
2025-02-19T00:19:51.808775image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 70956
18.2%
r 38986
 
10.0%
l 36341
 
9.3%
p 31962
 
8.2%
K 31296
 
8.0%
n 29679
 
7.6%
o 14202
 
3.7%
u 12470
 
3.2%
11874
 
3.1%
t 11870
 
3.1%
Other values (47) 99443
25.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 389079
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 70956
18.2%
r 38986
 
10.0%
l 36341
 
9.3%
p 31962
 
8.2%
K 31296
 
8.0%
n 29679
 
7.6%
o 14202
 
3.7%
u 12470
 
3.2%
11874
 
3.1%
t 11870
 
3.1%
Other values (47) 99443
25.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 389079
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 70956
18.2%
r 38986
 
10.0%
l 36341
 
9.3%
p 31962
 
8.2%
K 31296
 
8.0%
n 29679
 
7.6%
o 14202
 
3.7%
u 12470
 
3.2%
11874
 
3.1%
t 11870
 
3.1%
Other values (47) 99443
25.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 389079
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 70956
18.2%
r 38986
 
10.0%
l 36341
 
9.3%
p 31962
 
8.2%
K 31296
 
8.0%
n 29679
 
7.6%
o 14202
 
3.7%
u 12470
 
3.2%
11874
 
3.1%
t 11870
 
3.1%
Other values (47) 99443
25.6%
Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.6 MiB
2025-02-19T00:19:51.880251image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length46
Median length42
Mean length24.27497553
Min length7

Characters and Unicode

Total characters1116042
Distinct characters38
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowunknown
2nd rowunknown
3rd rowPublished Confirmed
4th rowPublished Confirmed
5th rowPublished Confirmed
ValueCountFrequency (%)
published 21030
18.0%
candidate 19167
16.4%
confirmed 18842
16.1%
project 16979
14.5%
kepler 15854
13.6%
unknown 7966
 
6.8%
q1_q17_dr25_sup_koi 2732
 
2.3%
q1_q16_koi 2721
 
2.3%
q1_q17_dr25_koi 2715
 
2.3%
q1_q17_dr24_koi 2701
 
2.3%
Other values (3) 6110
 
5.2%
2025-02-19T00:19:51.975777image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 107726
 
9.7%
d 86354
 
7.7%
i 74893
 
6.7%
70842
 
6.3%
n 61907
 
5.5%
r 59823
 
5.4%
o 59641
 
5.3%
_ 42588
 
3.8%
a 38334
 
3.4%
C 38009
 
3.4%
Other values (28) 475925
42.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1116042
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 107726
 
9.7%
d 86354
 
7.7%
i 74893
 
6.7%
70842
 
6.3%
n 61907
 
5.5%
r 59823
 
5.4%
o 59641
 
5.3%
_ 42588
 
3.8%
a 38334
 
3.4%
C 38009
 
3.4%
Other values (28) 475925
42.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1116042
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 107726
 
9.7%
d 86354
 
7.7%
i 74893
 
6.7%
70842
 
6.3%
n 61907
 
5.5%
r 59823
 
5.4%
o 59641
 
5.3%
_ 42588
 
3.8%
a 38334
 
3.4%
C 38009
 
3.4%
Other values (28) 475925
42.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1116042
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 107726
 
9.7%
d 86354
 
7.7%
i 74893
 
6.7%
70842
 
6.3%
n 61907
 
5.5%
r 59823
 
5.4%
o 59641
 
5.3%
_ 42588
 
3.8%
a 38334
 
3.4%
C 38009
 
3.4%
Other values (28) 475925
42.6%

pl_controv_flag
Real number (ℝ)

Skewed  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.001653072322
Minimum0
Maximum1
Zeros45899
Zeros (%)99.8%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:19:52.043154image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.04062481472
Coefficient of variation (CV)24.57534022
Kurtosis600.0012478
Mean0.001653072322
Median Absolute Deviation (MAD)0
Skewness24.53518181
Sum76
Variance0.001650375571
MonotonicityNot monotonic
2025-02-19T00:19:52.070710image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 45899
99.8%
1 76
 
0.2%
ValueCountFrequency (%)
0 45899
99.8%
1 76
 
0.2%
ValueCountFrequency (%)
1 76
 
0.2%
0 45899
99.8%
Distinct2007
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size3.3 MiB
2025-02-19T00:19:52.242504image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length44
Median length34
Mean length17.86453507
Min length7

Characters and Unicode

Total characters821322
Distinct characters69
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique906 ?
Unique (%)2.0%

Sample

1st rowunknown
2nd rowunknown
3rd row Kunitomo et al. 2011
4th row Liu et al. 2008
5th rowTeng et al. 2023
ValueCountFrequency (%)
et 18642
 
12.2%
al 18642
 
12.2%
koi 15854
 
10.4%
table 15854
 
10.4%
q1-q17 8148
 
5.3%
unknown 7966
 
5.2%
dr25 5447
 
3.6%
2016 4963
 
3.3%
2018 4291
 
2.8%
2019 2773
 
1.8%
Other values (1017) 50069
32.8%
2025-02-19T00:19:52.451620image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
110665
 
13.5%
e 54586
 
6.6%
a 51986
 
6.3%
1 46193
 
5.6%
l 46164
 
5.6%
n 39493
 
4.8%
2 38442
 
4.7%
Q 31737
 
3.9%
t 29938
 
3.6%
o 27993
 
3.4%
Other values (59) 344125
41.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 821322
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
110665
 
13.5%
e 54586
 
6.6%
a 51986
 
6.3%
1 46193
 
5.6%
l 46164
 
5.6%
n 39493
 
4.8%
2 38442
 
4.7%
Q 31737
 
3.9%
t 29938
 
3.6%
o 27993
 
3.4%
Other values (59) 344125
41.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 821322
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
110665
 
13.5%
e 54586
 
6.6%
a 51986
 
6.3%
1 46193
 
5.6%
l 46164
 
5.6%
n 39493
 
4.8%
2 38442
 
4.7%
Q 31737
 
3.9%
t 29938
 
3.6%
o 27993
 
3.4%
Other values (59) 344125
41.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 821322
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
110665
 
13.5%
e 54586
 
6.6%
a 51986
 
6.3%
1 46193
 
5.6%
l 46164
 
5.6%
n 39493
 
4.8%
2 38442
 
4.7%
Q 31737
 
3.9%
t 29938
 
3.6%
o 27993
 
3.4%
Other values (59) 344125
41.9%

planet_period_x
Real number (ℝ)

Skewed 

Distinct22049
Distinct (%)48.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9500.947839
Minimum0.09070629
Maximum402000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:19:52.515324image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.09070629
5-th percentile1.92279873
Q15.795296025
median10.35535888
Q318.74612075
95-th percentile158.6850878
Maximum402000000
Range401999999.9
Interquartile range (IQR)12.95082473

Descriptive statistics

Standard deviation1875934.193
Coefficient of variation (CV)197.4470574
Kurtosis45867.90375
Mean9500.947839
Median Absolute Deviation (MAD)5.43577508
Skewness214.0473503
Sum436806076.9
Variance3.519129097 × 1012
MonotonicityNot monotonic
2025-02-19T00:19:52.578771image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.35535888 11101
 
24.1%
38.2856338 7
 
< 0.1%
1.54167663 7
 
< 0.1%
7.07136076 6
 
< 0.1%
2.46106655 6
 
< 0.1%
5.28695437 6
 
< 0.1%
6.23853477 6
 
< 0.1%
25.09852783 6
 
< 0.1%
12.75802811 6
 
< 0.1%
5.96040108 6
 
< 0.1%
Other values (22039) 34818
75.7%
ValueCountFrequency (%)
0.09070629 1
< 0.1%
0.13293503 1
< 0.1%
0.179715 1
< 0.1%
0.179719 1
< 0.1%
0.2197 1
< 0.1%
ValueCountFrequency (%)
402000000 1
< 0.1%
8040000 1
< 0.1%
7300000 1
< 0.1%
5800000 2
< 0.1%
1790000 1
< 0.1%

pl_orbpererr1
Real number (ℝ)

Skewed 

Distinct7669
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10484.29474
Minimum0
Maximum470000000
Zeros9
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:19:52.638083image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.19 × 10-6
Q11.52 × 10-5
median3.8 × 10-5
Q39.541 × 10-5
95-th percentile0.0041
Maximum470000000
Range470000000
Interquartile range (IQR)8.021 × 10-5

Descriptive statistics

Standard deviation2192140.847
Coefficient of variation (CV)209.0880599
Kurtosis45961.57523
Mean10484.29474
Median Absolute Deviation (MAD)2.743 × 10-5
Skewness214.3710701
Sum482015450.7
Variance4.805481492 × 1012
MonotonicityNot monotonic
2025-02-19T00:19:52.785937image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.8 × 10-512677
 
27.6%
1 × 10-5117
 
0.3%
1 × 10-6110
 
0.2%
4 × 10-698
 
0.2%
0.00013 95
 
0.2%
0.00011 94
 
0.2%
3 × 10-690
 
0.2%
0.0001 88
 
0.2%
0.0002 87
 
0.2%
2 × 10-686
 
0.2%
Other values (7659) 32433
70.5%
ValueCountFrequency (%)
0 9
 
< 0.1%
1 × 10-86
 
< 0.1%
2 × 10-821
< 0.1%
3 × 10-821
< 0.1%
4 × 10-826
0.1%
ValueCountFrequency (%)
470000000 1
< 0.1%
3650000 1
< 0.1%
3000000 2
< 0.1%
830000 1
< 0.1%
470000 1
< 0.1%

pl_orbpererr2
Real number (ℝ)

Skewed 

Distinct7663
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-2469.401391
Minimum-100000000
Maximum0
Zeros8
Zeros (%)< 0.1%
Negative45967
Negative (%)> 99.9%
Memory size359.3 KiB
2025-02-19T00:19:52.844849image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-100000000
5-th percentile-0.004164
Q1-9.547 × 10-5
median-3.804 × 10-5
Q3-1.522 × 10-5
95-th percentile-1.19 × 10-6
Maximum0
Range100000000
Interquartile range (IQR)8.025 × 10-5

Descriptive statistics

Standard deviation467454.6813
Coefficient of variation (CV)-189.2987843
Kurtosis45553.08801
Mean-2469.401391
Median Absolute Deviation (MAD)2.745 × 10-5
Skewness-212.9770167
Sum-113530728.9
Variance2.185138791 × 1011
MonotonicityNot monotonic
2025-02-19T00:19:52.912868image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-3.804 × 10-512643
 
27.5%
-1 × 10-6113
 
0.2%
-1 × 10-5113
 
0.2%
-0.00013 103
 
0.2%
-0.00011 97
 
0.2%
-4 × 10-696
 
0.2%
-3 × 10-692
 
0.2%
-0.0001 91
 
0.2%
-2 × 10-686
 
0.2%
-0.0002 85
 
0.2%
Other values (7653) 32456
70.6%
ValueCountFrequency (%)
-100000000 1
< 0.1%
-4000000 2
< 0.1%
-3650000 1
< 0.1%
-830000 1
< 0.1%
-470000 1
< 0.1%
ValueCountFrequency (%)
0 8
 
< 0.1%
-1 × 10-86
 
< 0.1%
-2 × 10-821
< 0.1%
-3 × 10-820
< 0.1%
-4 × 10-826
0.1%

pl_orbperlim
Real number (ℝ)

Skewed  Zeros 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.0001740076128
Minimum-1
Maximum1
Zeros45961
Zeros (%)> 99.9%
Negative11
Negative (%)< 0.1%
Memory size359.3 KiB
2025-02-19T00:19:52.957310image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range2
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.01744963228
Coefficient of variation (CV)-100.2808555
Kurtosis3280.632849
Mean-0.0001740076128
Median Absolute Deviation (MAD)0
Skewness-32.72207607
Sum-8
Variance0.0003044896667
MonotonicityNot monotonic
2025-02-19T00:19:53.003168image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=3)
ValueCountFrequency (%)
0 45961
> 99.9%
-1 11
 
< 0.1%
1 3
 
< 0.1%
ValueCountFrequency (%)
-1 11
 
< 0.1%
0 45961
> 99.9%
1 3
 
< 0.1%
ValueCountFrequency (%)
1 3
 
< 0.1%
0 45961
> 99.9%
-1 11
 
< 0.1%

semi_major_axis_x
Real number (ℝ)

Skewed 

Distinct6351
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.241572524
Minimum0.0044
Maximum19000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:19:53.082249image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.0044
5-th percentile0.036751
Q10.1006
median0.1006
Q30.1006
95-th percentile0.7308
Maximum19000
Range18999.9956
Interquartile range (IQR)0

Descriptive statistics

Standard deviation124.9793059
Coefficient of variation (CV)55.75519178
Kurtosis14186.69374
Mean2.241572524
Median Absolute Deviation (MAD)0
Skewness109.3432131
Sum103056.2968
Variance15619.82691
MonotonicityNot monotonic
2025-02-19T00:19:53.164261image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1006 24511
53.3%
0.06 73
 
0.2%
0.052 61
 
0.1%
0.048 55
 
0.1%
0.051 55
 
0.1%
0.044 54
 
0.1%
0.05 53
 
0.1%
0.077 52
 
0.1%
0.049 49
 
0.1%
0.036 49
 
0.1%
Other values (6341) 20963
45.6%
ValueCountFrequency (%)
0.0044 1
 
< 0.1%
0.0058 3
< 0.1%
0.0059 1
 
< 0.1%
0.00598 1
 
< 0.1%
0.006 2
< 0.1%
ValueCountFrequency (%)
19000 1
< 0.1%
12000 1
< 0.1%
7506 1
< 0.1%
7493 1
< 0.1%
6100 1
< 0.1%

pl_orbsmaxerr1
Real number (ℝ)

Skewed 

Distinct982
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1667517588
Minimum0
Maximum5205
Zeros76
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:19:53.225720image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.00099
Q10.002
median0.002
Q30.002
95-th percentile0.0067
Maximum5205
Range5205
Interquartile range (IQR)0

Descriptive statistics

Standard deviation24.33874211
Coefficient of variation (CV)145.9579335
Kurtosis45493.85136
Mean0.1667517588
Median Absolute Deviation (MAD)0
Skewness212.7638375
Sum7666.41211
Variance592.3743677
MonotonicityNot monotonic
2025-02-19T00:19:53.291234image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.002 39109
85.1%
0.001 248
 
0.5%
0.02 113
 
0.2%
0.003 111
 
0.2%
0.0011 93
 
0.2%
0.0012 92
 
0.2%
0.0008 83
 
0.2%
0.004 78
 
0.2%
0.0006 77
 
0.2%
0.03 77
 
0.2%
Other values (972) 5894
 
12.8%
ValueCountFrequency (%)
0 76
0.2%
1 × 10-65
 
< 0.1%
2 × 10-63
 
< 0.1%
3 × 10-61
 
< 0.1%
4 × 10-62
 
< 0.1%
ValueCountFrequency (%)
5205 1
< 0.1%
200 2
< 0.1%
114.5 1
< 0.1%
110 2
< 0.1%
60 2
< 0.1%

pl_orbsmaxerr2
Real number (ℝ)

Skewed 

Distinct973
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.1113137431
Minimum-2060
Maximum0
Zeros77
Zeros (%)0.2%
Negative45898
Negative (%)99.8%
Memory size359.3 KiB
2025-02-19T00:19:53.347152image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-2060
5-th percentile-0.007
Q1-0.002
median-0.002
Q3-0.002
95-th percentile-0.001
Maximum0
Range2060
Interquartile range (IQR)0

Descriptive statistics

Standard deviation10.47917371
Coefficient of variation (CV)-94.14087973
Kurtosis33260.45557
Mean-0.1113137431
Median Absolute Deviation (MAD)0
Skewness-175.7084374
Sum-5117.649341
Variance109.8130816
MonotonicityNot monotonic
2025-02-19T00:19:53.430784image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.002 39103
85.1%
-0.001 246
 
0.5%
-0.02 109
 
0.2%
-0.003 108
 
0.2%
-0.0011 99
 
0.2%
-0.0012 98
 
0.2%
-0.0005 80
 
0.2%
-0.004 80
 
0.2%
-0.01 79
 
0.2%
0 77
 
0.2%
Other values (963) 5896
 
12.8%
ValueCountFrequency (%)
-2060 1
< 0.1%
-810 1
< 0.1%
-200 2
< 0.1%
-150 2
< 0.1%
-60 2
< 0.1%
ValueCountFrequency (%)
0 77
0.2%
-1 × 10-65
 
< 0.1%
-2 × 10-63
 
< 0.1%
-3 × 10-61
 
< 0.1%
-4 × 10-62
 
< 0.1%

pl_orbsmaxlim
Real number (ℝ)

Skewed  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-6.525285481 × 10-5
Minimum-1
Maximum0
Zeros45972
Zeros (%)> 99.9%
Negative3
Negative (%)< 0.1%
Memory size359.3 KiB
2025-02-19T00:19:53.500548image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.008077748209
Coefficient of variation (CV)-123.7914913
Kurtosis15321.66645
Mean-6.525285481 × 10-5
Median Absolute Deviation (MAD)0
Skewness-123.7861056
Sum-3
Variance6.525001613 × 10-5
MonotonicityNot monotonic
2025-02-19T00:19:53.543835image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 45972
> 99.9%
-1 3
 
< 0.1%
ValueCountFrequency (%)
-1 3
 
< 0.1%
0 45972
> 99.9%
ValueCountFrequency (%)
0 45972
> 99.9%
-1 3
 
< 0.1%

planet_radius_x
Real number (ℝ)

Skewed 

Distinct4942
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.088546819
Minimum0.27
Maximum4282.98
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:19:53.603383image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.27
5-th percentile1.12
Q12.1
median2.29
Q32.47
95-th percentile11.321
Maximum4282.98
Range4282.71
Interquartile range (IQR)0.37

Descriptive statistics

Standard deviation55.13006713
Coefficient of variation (CV)13.48402491
Kurtosis3887.173733
Mean4.088546819
Median Absolute Deviation (MAD)0.189
Skewness60.95451404
Sum187970.94
Variance3039.324302
MonotonicityNot monotonic
2025-02-19T00:19:53.659940image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.29 19665
42.8%
2.2 139
 
0.3%
2.5 134
 
0.3%
2.6 122
 
0.3%
2.3 120
 
0.3%
1.32 119
 
0.3%
2.4 118
 
0.3%
2.8 115
 
0.3%
1.5 114
 
0.2%
1.48 114
 
0.2%
Other values (4932) 25215
54.8%
ValueCountFrequency (%)
0.27 2
< 0.1%
0.276 2
< 0.1%
0.277 1
< 0.1%
0.296 1
< 0.1%
0.303 1
< 0.1%
ValueCountFrequency (%)
4282.98 1
 
< 0.1%
3791.05 3
< 0.1%
3690.889 1
 
< 0.1%
3163.54 3
< 0.1%
2783.7 3
< 0.1%

pl_radeerr1
Real number (ℝ)

Skewed 

Distinct1554
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.286215356
Minimum0
Maximum8872.156
Zeros15
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:19:53.710531image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.08
Q10.314
median0.372
Q30.45
95-th percentile1.457
Maximum8872.156
Range8872.156
Interquartile range (IQR)0.136

Descriptive statistics

Standard deviation57.06429531
Coefficient of variation (CV)44.36605039
Kurtosis17620.50389
Mean1.286215356
Median Absolute Deviation (MAD)0.068
Skewness125.1414213
Sum59133.751
Variance3256.333799
MonotonicityNot monotonic
2025-02-19T00:19:53.750001image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.372 20316
44.2%
0.1 353
 
0.8%
0.12 340
 
0.7%
0.2 336
 
0.7%
0.13 329
 
0.7%
0.11 319
 
0.7%
0.14 314
 
0.7%
0.09 308
 
0.7%
0.17 296
 
0.6%
0.08 291
 
0.6%
Other values (1544) 22773
49.5%
ValueCountFrequency (%)
0 15
< 0.1%
0.002 3
 
< 0.1%
0.006 1
 
< 0.1%
0.01 13
< 0.1%
0.011 1
 
< 0.1%
ValueCountFrequency (%)
8872.156 1
 
< 0.1%
6958.076 1
 
< 0.1%
1916.293 1
 
< 0.1%
1793.904 1
 
< 0.1%
1666.92 3
< 0.1%

pl_radeerr2
Real number (ℝ)

Skewed 

Distinct1388
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.5349940837
Minimum-1916.293
Maximum0
Zeros17
Zeros (%)< 0.1%
Negative45958
Negative (%)> 99.9%
Memory size359.3 KiB
2025-02-19T00:19:53.908555image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-1916.293
5-th percentile-1.009
Q1-0.247
median-0.22
Q3-0.196
95-th percentile-0.07
Maximum0
Range1916.293
Interquartile range (IQR)0.051

Descriptive statistics

Standard deviation14.44350298
Coefficient of variation (CV)-26.99750038
Kurtosis12892.78319
Mean-0.5349940837
Median Absolute Deviation (MAD)0.026
Skewness-107.738839
Sum-24596.353
Variance208.6147784
MonotonicityNot monotonic
2025-02-19T00:19:53.986643image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.22 20731
45.1%
-0.1 639
 
1.4%
-0.12 633
 
1.4%
-0.11 622
 
1.4%
-0.14 603
 
1.3%
-0.13 591
 
1.3%
-0.16 586
 
1.3%
-0.2 562
 
1.2%
-0.09 547
 
1.2%
-0.19 538
 
1.2%
Other values (1378) 19923
43.3%
ValueCountFrequency (%)
-1916.293 1
< 0.1%
-1793.904 1
< 0.1%
-1089.608 1
< 0.1%
-840.815 1
< 0.1%
-430.35 1
< 0.1%
ValueCountFrequency (%)
0 17
< 0.1%
-0.002 3
 
< 0.1%
-0.005 1
 
< 0.1%
-0.008 1
 
< 0.1%
-0.01 8
< 0.1%

pl_radelim
Real number (ℝ)

Skewed  Zeros 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-8.700380642 × 10-5
Minimum-1
Maximum1
Zeros45969
Zeros (%)> 99.9%
Negative5
Negative (%)< 0.1%
Memory size359.3 KiB
2025-02-19T00:19:54.052147image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range2
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.01142370249
Coefficient of variation (CV)-131.3011804
Kurtosis7659.444436
Mean-8.700380642 × 10-5
Median Absolute Deviation (MAD)0
Skewness-58.34127022
Sum-4
Variance0.0001305009785
MonotonicityNot monotonic
2025-02-19T00:19:54.097993image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=3)
ValueCountFrequency (%)
0 45969
> 99.9%
-1 5
 
< 0.1%
1 1
 
< 0.1%
ValueCountFrequency (%)
-1 5
 
< 0.1%
0 45969
> 99.9%
1 1
 
< 0.1%
ValueCountFrequency (%)
1 1
 
< 0.1%
0 45969
> 99.9%
-1 5
 
< 0.1%

pl_radj
Real number (ℝ)

Skewed 

Distinct1618
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3646412181
Minimum0.024
Maximum382.103
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:19:54.159334image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.024
5-th percentile0.1
Q10.187
median0.204
Q30.22
95-th percentile1.0103
Maximum382.103
Range382.079
Interquartile range (IQR)0.033

Descriptive statistics

Standard deviation4.918391309
Coefficient of variation (CV)13.4883032
Kurtosis3887.160906
Mean0.3646412181
Median Absolute Deviation (MAD)0.016
Skewness60.95437607
Sum16764.38
Variance24.19057307
MonotonicityNot monotonic
2025-02-19T00:19:54.230566image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.204 19687
42.8%
0.136 183
 
0.4%
0.17 176
 
0.4%
0.128 173
 
0.4%
0.178 173
 
0.4%
0.12 171
 
0.4%
0.194 170
 
0.4%
0.112 168
 
0.4%
0.103 168
 
0.4%
0.145 165
 
0.4%
Other values (1608) 24741
53.8%
ValueCountFrequency (%)
0.024 2
< 0.1%
0.025 3
< 0.1%
0.026 1
 
< 0.1%
0.027 1
 
< 0.1%
0.028 4
< 0.1%
ValueCountFrequency (%)
382.103 1
 
< 0.1%
338.215 3
< 0.1%
329.28 1
 
< 0.1%
282.233 3
< 0.1%
248.346 3
< 0.1%

pl_radjerr1
Real number (ℝ)

Skewed 

Distinct515
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1146698423
Minimum0
Maximum791.521
Zeros18
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:19:54.286314image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.007
Q10.028
median0.033
Q30.04
95-th percentile0.13
Maximum791.521
Range791.521
Interquartile range (IQR)0.012

Descriptive statistics

Standard deviation5.090939997
Coefficient of variation (CV)44.39650299
Kurtosis17620.46748
Mean0.1146698423
Median Absolute Deviation (MAD)0.006
Skewness125.14125
Sum5271.946
Variance25.91767005
MonotonicityNot monotonic
2025-02-19T00:19:54.333748image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.033 20483
44.6%
0.012 805
 
1.8%
0.007 637
 
1.4%
0.009 604
 
1.3%
0.006 581
 
1.3%
0.008 562
 
1.2%
0.011 554
 
1.2%
0.021 551
 
1.2%
0.01 544
 
1.2%
0.004 539
 
1.2%
Other values (505) 20115
43.8%
ValueCountFrequency (%)
0 18
 
< 0.1%
0.001 28
 
0.1%
0.002 119
 
0.3%
0.003 236
0.5%
0.004 539
1.2%
ValueCountFrequency (%)
791.521 1
 
< 0.1%
620.758 1
 
< 0.1%
170.961 1
 
< 0.1%
160.042 1
 
< 0.1%
148.713 3
< 0.1%

pl_radjerr2
Real number (ℝ)

Skewed 

Distinct406
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.0478994236
Minimum-170.961
Maximum0
Zeros21
Zeros (%)< 0.1%
Negative45954
Negative (%)> 99.9%
Memory size359.3 KiB
2025-02-19T00:19:54.433218image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-170.961
5-th percentile-0.09
Q1-0.022
median-0.02
Q3-0.018
95-th percentile-0.006
Maximum0
Range170.961
Interquartile range (IQR)0.004

Descriptive statistics

Standard deviation1.288563789
Coefficient of variation (CV)-26.90144667
Kurtosis12892.88252
Mean-0.0478994236
Median Absolute Deviation (MAD)0.002
Skewness-107.7392565
Sum-2202.176
Variance1.660396639
MonotonicityNot monotonic
2025-02-19T00:19:54.540969image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.02 20896
45.5%
-0.012 1365
 
3.0%
-0.01 885
 
1.9%
-0.009 879
 
1.9%
-0.011 851
 
1.9%
-0.008 842
 
1.8%
-0.021 823
 
1.8%
-0.007 809
 
1.8%
-0.006 752
 
1.6%
-0.014 734
 
1.6%
Other values (396) 17139
37.3%
ValueCountFrequency (%)
-170.961 1
< 0.1%
-160.042 1
< 0.1%
-97.208 1
< 0.1%
-75.012 1
< 0.1%
-38.393 1
< 0.1%
ValueCountFrequency (%)
0 21
 
< 0.1%
-0.001 26
 
0.1%
-0.002 135
 
0.3%
-0.003 285
0.6%
-0.004 695
1.5%

pl_radjlim
Real number (ℝ)

Skewed  Zeros 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-8.700380642 × 10-5
Minimum-1
Maximum1
Zeros45969
Zeros (%)> 99.9%
Negative5
Negative (%)< 0.1%
Memory size359.3 KiB
2025-02-19T00:19:54.588611image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range2
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.01142370249
Coefficient of variation (CV)-131.3011804
Kurtosis7659.444436
Mean-8.700380642 × 10-5
Median Absolute Deviation (MAD)0
Skewness-58.34127022
Sum-4
Variance0.0001305009785
MonotonicityNot monotonic
2025-02-19T00:19:54.652364image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=3)
ValueCountFrequency (%)
0 45969
> 99.9%
-1 5
 
< 0.1%
1 1
 
< 0.1%
ValueCountFrequency (%)
-1 5
 
< 0.1%
0 45969
> 99.9%
1 1
 
< 0.1%
ValueCountFrequency (%)
1 1
 
< 0.1%
0 45969
> 99.9%
-1 5
 
< 0.1%

pl_bmasse
Real number (ℝ)

Distinct4026
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean282.9227996
Minimum0.015
Maximum25426.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:19:54.707675image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.015
5-th percentile73.100789
Q1210
median210
Q3210
95-th percentile403.9615
Maximum25426.4
Range25426.385
Interquartile range (IQR)0

Descriptive statistics

Standard deviation576.022868
Coefficient of variation (CV)2.035971894
Kurtosis265.3699751
Mean282.9227996
Median Absolute Deviation (MAD)0
Skewness12.76092448
Sum13007375.71
Variance331802.3445
MonotonicityNot monotonic
2025-02-19T00:19:54.763582image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
210 39703
86.4%
4 17
 
< 0.1%
5.6 11
 
< 0.1%
15.2 11
 
< 0.1%
9 11
 
< 0.1%
8 10
 
< 0.1%
3.9 10
 
< 0.1%
266.9772 10
 
< 0.1%
4.3 10
 
< 0.1%
6.1 10
 
< 0.1%
Other values (4016) 6172
 
13.4%
ValueCountFrequency (%)
0.015 1
< 0.1%
0.02 1
< 0.1%
0.0275 1
< 0.1%
0.0479 1
< 0.1%
0.065 1
< 0.1%
ValueCountFrequency (%)
25426.4 1
< 0.1%
22934.49785 1
< 0.1%
17668.1697 1
< 0.1%
15452.81715 1
< 0.1%
13762.039 1
< 0.1%

pl_bmasseerr1
Real number (ℝ)

Skewed 

Distinct1798
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.90887209
Minimum0
Maximum24965.5465
Zeros9
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:19:54.819549image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10.80622
Q119.0697
median19.0697
Q319.0697
95-th percentile29.239363
Maximum24965.5465
Range24965.5465
Interquartile range (IQR)0

Descriptive statistics

Standard deviation258.0749435
Coefficient of variation (CV)6.992219726
Kurtosis2630.443122
Mean36.90887209
Median Absolute Deviation (MAD)0
Skewness40.93112913
Sum1696885.394
Variance66602.67645
MonotonicityNot monotonic
2025-02-19T00:19:54.874706image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19.0697 40240
87.5%
38.1396 42
 
0.1%
31.783 40
 
0.1%
9.5349 37
 
0.1%
25.4264 37
 
0.1%
1.7 36
 
0.1%
34.9613 35
 
0.1%
41.3179 34
 
0.1%
22.2481 34
 
0.1%
1.3 32
 
0.1%
Other values (1788) 5408
 
11.8%
ValueCountFrequency (%)
0 9
< 0.1%
0.002 1
 
< 0.1%
0.0051 1
 
< 0.1%
0.0079 1
 
< 0.1%
0.012 1
 
< 0.1%
ValueCountFrequency (%)
24965.5465 1
< 0.1%
13030.96469 1
< 0.1%
12395.30787 1
< 0.1%
10234.126 1
< 0.1%
9757.381 1
< 0.1%

pl_bmasseerr2
Real number (ℝ)

Skewed 

Distinct1721
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-30.98133529
Minimum-24965.5465
Maximum3.34
Zeros10
Zeros (%)< 0.1%
Negative45963
Negative (%)> 99.9%
Memory size359.3 KiB
2025-02-19T00:19:54.925299image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-24965.5465
5-th percentile-28.6
Q1-17.79848
median-17.79848
Q3-17.79848
95-th percentile-10.17051
Maximum3.34
Range24968.8865
Interquartile range (IQR)0

Descriptive statistics

Standard deviation193.3634563
Coefficient of variation (CV)-6.241288651
Kurtosis6565.396381
Mean-30.98133529
Median Absolute Deviation (MAD)0
Skewness-62.18485982
Sum-1424366.89
Variance37389.42624
MonotonicityNot monotonic
2025-02-19T00:19:55.008839image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-17.79848 40240
87.5%
-38.1396 44
 
0.1%
-31.783 43
 
0.1%
-9.5349 40
 
0.1%
-2 36
 
0.1%
-1.3 34
 
0.1%
-25.4264 34
 
0.1%
-44.4962 34
 
0.1%
-12.7132 33
 
0.1%
-34.9613 33
 
0.1%
Other values (1711) 5404
 
11.8%
ValueCountFrequency (%)
-24965.5465 1
< 0.1%
-10265.909 1
< 0.1%
-9757.381 1
< 0.1%
-7310.05336 1
< 0.1%
-6941.37241 1
< 0.1%
ValueCountFrequency (%)
3.34 1
 
< 0.1%
0.29 1
 
< 0.1%
0 10
< 0.1%
-0.002 1
 
< 0.1%
-0.0041 1
 
< 0.1%

pl_bmasselim
Real number (ℝ)

Zeros 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.004893964111
Minimum-1
Maximum1
Zeros45724
Zeros (%)99.5%
Negative13
Negative (%)< 0.1%
Memory size359.3 KiB
2025-02-19T00:19:55.049929image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range2
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.07372690281
Coefficient of variation (CV)15.06486381
Kurtosis178.5885113
Mean0.004893964111
Median Absolute Deviation (MAD)0
Skewness12.01324479
Sum225
Variance0.005435656199
MonotonicityNot monotonic
2025-02-19T00:19:55.171126image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=3)
ValueCountFrequency (%)
0 45724
99.5%
1 238
 
0.5%
-1 13
 
< 0.1%
ValueCountFrequency (%)
-1 13
 
< 0.1%
0 45724
99.5%
1 238
 
0.5%
ValueCountFrequency (%)
1 238
 
0.5%
0 45724
99.5%
-1 13
 
< 0.1%

pl_bmassj
Real number (ℝ)

Distinct3009
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.8912813344
Minimum5 × 10-5
Maximum80
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:19:55.208429image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum5 × 10-5
5-th percentile0.23
Q10.662
median0.662
Q30.662
95-th percentile1.27
Maximum80
Range79.99995
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.812207311
Coefficient of variation (CV)2.033260701
Kurtosis265.4322994
Mean0.8912813344
Median Absolute Deviation (MAD)0
Skewness12.76254156
Sum40976.65935
Variance3.284095338
MonotonicityNot monotonic
2025-02-19T00:19:55.272232image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.662 39704
86.4%
1.8 21
 
< 0.1%
0.4 19
 
< 0.1%
2.3 19
 
< 0.1%
1.5 16
 
< 0.1%
0.56 16
 
< 0.1%
0.84 15
 
< 0.1%
0.01259 14
 
< 0.1%
2 14
 
< 0.1%
2.2 14
 
< 0.1%
Other values (2999) 6123
 
13.3%
ValueCountFrequency (%)
5 × 10-51
< 0.1%
6 × 10-51
< 0.1%
9 × 10-51
< 0.1%
0.00015 1
< 0.1%
0.0002 1
< 0.1%
ValueCountFrequency (%)
80 1
< 0.1%
72.16 1
< 0.1%
55.59 1
< 0.1%
48.62 1
< 0.1%
43.3 1
< 0.1%

pl_bmassjerr1
Real number (ℝ)

Skewed 

Distinct1169
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1161334097
Minimum0
Maximum78.55
Zeros4
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:19:55.325770image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.035
Q10.06
median0.06
Q30.06
95-th percentile0.092
Maximum78.55
Range78.55
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.8123653314
Coefficient of variation (CV)6.995104455
Kurtosis2627.0553
Mean0.1161334097
Median Absolute Deviation (MAD)0
Skewness40.91887394
Sum5339.23351
Variance0.6599374316
MonotonicityNot monotonic
2025-02-19T00:19:55.384741image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.06 40299
87.7%
0.1 95
 
0.2%
0.03 91
 
0.2%
0.13 77
 
0.2%
0.12 77
 
0.2%
0.07 72
 
0.2%
0.05 72
 
0.2%
0.02 71
 
0.2%
0.2 68
 
0.1%
0.04 68
 
0.1%
Other values (1159) 4985
 
10.8%
ValueCountFrequency (%)
0 4
< 0.1%
1 × 10-51
 
< 0.1%
2 × 10-52
< 0.1%
4 × 10-51
 
< 0.1%
6 × 10-52
< 0.1%
ValueCountFrequency (%)
78.55 1
< 0.1%
41 1
< 0.1%
39 1
< 0.1%
32.2 1
< 0.1%
30.7 1
< 0.1%

pl_bmassjerr2
Real number (ℝ)

Skewed 

Distinct1089
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.09747916803
Minimum-78.55
Maximum0.0105
Zeros5
Zeros (%)< 0.1%
Negative45968
Negative (%)> 99.9%
Memory size359.3 KiB
2025-02-19T00:19:55.429841image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-78.55
5-th percentile-0.09
Q1-0.056
median-0.056
Q3-0.056
95-th percentile-0.032
Maximum0.0105
Range78.5605
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.6083189993
Coefficient of variation (CV)-6.240502577
Kurtosis6568.272455
Mean-0.09747916803
Median Absolute Deviation (MAD)0
Skewness-62.20276697
Sum-4481.60475
Variance0.3700520049
MonotonicityNot monotonic
2025-02-19T00:19:55.493601image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.056 40257
87.6%
-0.1 93
 
0.2%
-0.03 91
 
0.2%
-0.04 79
 
0.2%
-0.2 77
 
0.2%
-0.12 76
 
0.2%
-0.13 75
 
0.2%
-0.08 72
 
0.2%
-0.06 72
 
0.2%
-0.11 71
 
0.2%
Other values (1079) 5012
 
10.9%
ValueCountFrequency (%)
-78.55 1
< 0.1%
-32.3 1
< 0.1%
-30.7 1
< 0.1%
-23 1
< 0.1%
-21.84 1
< 0.1%
ValueCountFrequency (%)
0.0105 1
 
< 0.1%
0.0009 1
 
< 0.1%
0 5
< 0.1%
-1 × 10-52
 
< 0.1%
-2 × 10-51
 
< 0.1%

pl_bmassjlim
Real number (ℝ)

Zeros 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.004893964111
Minimum-1
Maximum1
Zeros45724
Zeros (%)99.5%
Negative13
Negative (%)< 0.1%
Memory size359.3 KiB
2025-02-19T00:19:55.557055image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range2
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.07372690281
Coefficient of variation (CV)15.06486381
Kurtosis178.5885113
Mean0.004893964111
Median Absolute Deviation (MAD)0
Skewness12.01324479
Sum225
Variance0.005435656199
MonotonicityNot monotonic
2025-02-19T00:19:55.610853image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=3)
ValueCountFrequency (%)
0 45724
99.5%
1 238
 
0.5%
-1 13
 
< 0.1%
ValueCountFrequency (%)
-1 13
 
< 0.1%
0 45724
99.5%
1 238
 
0.5%
ValueCountFrequency (%)
1 238
 
0.5%
0 45724
99.5%
-1 13
 
< 0.1%
Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.8 MiB
2025-02-19T00:19:55.652026image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length14
Median length7
Mean length6.6445677
Min length4

Characters and Unicode

Total characters305484
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowunknown
2nd rowunknown
3rd rowMsini
4th rowMsini
5th rowMsini
ValueCountFrequency (%)
unknown 39701
86.4%
mass 4054
 
8.8%
msini 2191
 
4.8%
msin(i)/sin(i 29
 
0.1%
2025-02-19T00:19:55.731221image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 121352
39.7%
u 39701
 
13.0%
k 39701
 
13.0%
o 39701
 
13.0%
w 39701
 
13.0%
s 10357
 
3.4%
M 6274
 
2.1%
i 4498
 
1.5%
a 4054
 
1.3%
( 58
 
< 0.1%
Other values (2) 87
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 305484
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 121352
39.7%
u 39701
 
13.0%
k 39701
 
13.0%
o 39701
 
13.0%
w 39701
 
13.0%
s 10357
 
3.4%
M 6274
 
2.1%
i 4498
 
1.5%
a 4054
 
1.3%
( 58
 
< 0.1%
Other values (2) 87
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 305484
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 121352
39.7%
u 39701
 
13.0%
k 39701
 
13.0%
o 39701
 
13.0%
w 39701
 
13.0%
s 10357
 
3.4%
M 6274
 
2.1%
i 4498
 
1.5%
a 4054
 
1.3%
( 58
 
< 0.1%
Other values (2) 87
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 305484
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 121352
39.7%
u 39701
 
13.0%
k 39701
 
13.0%
o 39701
 
13.0%
w 39701
 
13.0%
s 10357
 
3.4%
M 6274
 
2.1%
i 4498
 
1.5%
a 4054
 
1.3%
( 58
 
< 0.1%
Other values (2) 87
 
< 0.1%

pl_orbeccen
Real number (ℝ)

Zeros 

Distinct911
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0177781595
Minimum0
Maximum0.97
Zeros41874
Zeros (%)91.1%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:19:55.778521image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.11
Maximum0.97
Range0.97
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.0810506795
Coefficient of variation (CV)4.559002831
Kurtosis44.74721018
Mean0.0177781595
Median Absolute Deviation (MAD)0
Skewness6.211671477
Sum817.350883
Variance0.006569212647
MonotonicityNot monotonic
2025-02-19T00:19:55.843787image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 41874
91.1%
0.12 69
 
0.2%
0.04 68
 
0.1%
0.07 66
 
0.1%
0.02 64
 
0.1%
0.05 64
 
0.1%
0.11 62
 
0.1%
0.06 62
 
0.1%
0.2 61
 
0.1%
0.03 60
 
0.1%
Other values (901) 3525
 
7.7%
ValueCountFrequency (%)
0 41874
91.1%
8 × 10-51
 
< 0.1%
0.0001 1
 
< 0.1%
0.00016 1
 
< 0.1%
0.0002 1
 
< 0.1%
ValueCountFrequency (%)
0.97 1
< 0.1%
0.956 1
< 0.1%
0.95 2
< 0.1%
0.948 1
< 0.1%
0.9412 1
< 0.1%

pl_orbeccenlim
Real number (ℝ)

Zeros 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.01268080479
Minimum-1
Maximum9
Zeros45376
Zeros (%)98.7%
Negative12
Negative (%)< 0.1%
Memory size359.3 KiB
2025-02-19T00:19:55.886574image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum9
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.12086526
Coefficient of variation (CV)9.531355624
Kurtosis720.106898
Mean0.01268080479
Median Absolute Deviation (MAD)0
Skewness15.73672367
Sum583
Variance0.01460841108
MonotonicityNot monotonic
2025-02-19T00:19:55.933708image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=4)
ValueCountFrequency (%)
0 45376
98.7%
1 586
 
1.3%
-1 12
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
-1 12
 
< 0.1%
0 45376
98.7%
1 586
 
1.3%
9 1
 
< 0.1%
ValueCountFrequency (%)
9 1
 
< 0.1%
1 586
 
1.3%
0 45376
98.7%
-1 12
 
< 0.1%

pl_insol
Real number (ℝ)

Skewed 

Distinct8507
Distinct (%)18.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean185.3574854
Minimum0
Maximum58192.75
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:19:55.981056image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9.14
Q185.48
median85.48
Q385.48
95-th percentile596.16
Maximum58192.75
Range58192.75
Interquartile range (IQR)0

Descriptive statistics

Standard deviation852.2712863
Coefficient of variation (CV)4.597986882
Kurtosis2111.554014
Mean185.3574854
Median Absolute Deviation (MAD)0
Skewness38.57508531
Sum8521810.39
Variance726366.3455
MonotonicityNot monotonic
2025-02-19T00:19:56.060453image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
85.48 29267
63.7%
1.31 14
 
< 0.1%
4.9 13
 
< 0.1%
5.55 12
 
< 0.1%
4.4 12
 
< 0.1%
1.21 12
 
< 0.1%
21.4 12
 
< 0.1%
0.39 11
 
< 0.1%
7.29 11
 
< 0.1%
2.14 11
 
< 0.1%
Other values (8497) 16600
36.1%
ValueCountFrequency (%)
0 1
< 0.1%
0.01 1
< 0.1%
0.02 2
< 0.1%
0.03 1
< 0.1%
0.05 1
< 0.1%
ValueCountFrequency (%)
58192.75 3
< 0.1%
44900 1
 
< 0.1%
38711.5 1
 
< 0.1%
37958.27 4
< 0.1%
33326.73 1
 
< 0.1%

pl_insolerr1
Real number (ℝ)

Skewed 

Distinct5625
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean101.1901546
Minimum0
Maximum48504.39
Zeros27
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:19:56.126277image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.1
Q127.86
median27.86
Q327.86
95-th percentile307.576
Maximum48504.39
Range48504.39
Interquartile range (IQR)0

Descriptive statistics

Standard deviation724.856548
Coefficient of variation (CV)7.163311001
Kurtosis2401.150381
Mean101.1901546
Median Absolute Deviation (MAD)0
Skewness41.58030544
Sum4652217.36
Variance525417.0152
MonotonicityNot monotonic
2025-02-19T00:19:56.251305image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27.86 30439
66.2%
0.2 61
 
0.1%
1.1 43
 
0.1%
0.1 42
 
0.1%
0.5 41
 
0.1%
0.3 39
 
0.1%
2.1 36
 
0.1%
0.7 35
 
0.1%
1.6 34
 
0.1%
0.09 32
 
0.1%
Other values (5615) 15173
33.0%
ValueCountFrequency (%)
0 27
0.1%
0.01 24
0.1%
0.02 16
< 0.1%
0.03 16
< 0.1%
0.04 10
 
< 0.1%
ValueCountFrequency (%)
48504.39 3
< 0.1%
44636.82 3
< 0.1%
32770.23 1
 
< 0.1%
17366.35 3
< 0.1%
16417.88 3
< 0.1%

pl_insolerr2
Real number (ℝ)

Skewed 

Distinct4840
Distinct (%)10.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-39.10436237
Minimum-28302.96
Maximum0
Zeros27
Zeros (%)0.1%
Negative45948
Negative (%)99.9%
Memory size359.3 KiB
2025-02-19T00:19:56.326279image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-28302.96
5-th percentile-109.35
Q1-13.7
median-13.7
Q3-13.7
95-th percentile-1.46
Maximum0
Range28302.96
Interquartile range (IQR)0

Descriptive statistics

Standard deviation315.4671605
Coefficient of variation (CV)-8.067313756
Kurtosis3697.748982
Mean-39.10436237
Median Absolute Deviation (MAD)0
Skewness-52.95627662
Sum-1797823.06
Variance99519.52934
MonotonicityNot monotonic
2025-02-19T00:19:56.400164image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-13.7 30436
66.2%
-0.2 61
 
0.1%
-0.1 48
 
0.1%
-1.1 47
 
0.1%
-0.5 41
 
0.1%
-0.3 40
 
0.1%
-1.6 40
 
0.1%
-0.6 39
 
0.1%
-2.1 35
 
0.1%
-1.2 34
 
0.1%
Other values (4830) 15154
33.0%
ValueCountFrequency (%)
-28302.96 1
 
< 0.1%
-23093.53 3
< 0.1%
-15541.42 1
 
< 0.1%
-13917.83 3
< 0.1%
-7977.74 1
 
< 0.1%
ValueCountFrequency (%)
0 27
0.1%
-0.01 24
0.1%
-0.02 19
< 0.1%
-0.03 15
< 0.1%
-0.04 13
< 0.1%

pl_insollim
Real number (ℝ)

Constant  Zeros 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros45975
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:19:56.426229image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-02-19T00:19:56.457695image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 45975
100.0%
ValueCountFrequency (%)
0 45975
100.0%
ValueCountFrequency (%)
0 45975
100.0%

pl_eqt
Real number (ℝ)

Distinct1926
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean824.5989125
Minimum34
Maximum4050
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:19:56.505396image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum34
5-th percentile458
Q1795
median795
Q3795
95-th percentile1322
Maximum4050
Range4016
Interquartile range (IQR)0

Descriptive statistics

Standard deviation259.4240022
Coefficient of variation (CV)0.3146062871
Kurtosis14.32190788
Mean824.5989125
Median Absolute Deviation (MAD)0
Skewness2.585975252
Sum37910935
Variance67300.81289
MonotonicityNot monotonic
2025-02-19T00:19:56.586727image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
795 29337
63.8%
767 42
 
0.1%
583 35
 
0.1%
613 32
 
0.1%
770 32
 
0.1%
674 32
 
0.1%
487 31
 
0.1%
752 30
 
0.1%
946 30
 
0.1%
694 29
 
0.1%
Other values (1916) 16345
35.6%
ValueCountFrequency (%)
34 1
< 0.1%
50 1
< 0.1%
55 2
< 0.1%
59 1
< 0.1%
71 2
< 0.1%
ValueCountFrequency (%)
4050 1
 
< 0.1%
3961 3
< 0.1%
3907 1
 
< 0.1%
3866 1
 
< 0.1%
3646 1
 
< 0.1%

pl_eqtlim
Real number (ℝ)

Skewed  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.525285481 × 10-5
Minimum0
Maximum1
Zeros45972
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:19:56.649121image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.008077748209
Coefficient of variation (CV)123.7914913
Kurtosis15321.66645
Mean6.525285481 × 10-5
Median Absolute Deviation (MAD)0
Skewness123.7861056
Sum3
Variance6.525001613 × 10-5
MonotonicityNot monotonic
2025-02-19T00:19:56.680756image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 45972
> 99.9%
1 3
 
< 0.1%
ValueCountFrequency (%)
0 45972
> 99.9%
1 3
 
< 0.1%
ValueCountFrequency (%)
1 3
 
< 0.1%
0 45972
> 99.9%

ttv_flag
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.09028820011
Minimum0
Maximum1
Zeros41824
Zeros (%)91.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:19:56.712064image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2865973266
Coefficient of variation (CV)3.174250082
Kurtosis6.175695777
Mean0.09028820011
Median Absolute Deviation (MAD)0
Skewness2.859270383
Sum4151
Variance0.08213802761
MonotonicityNot monotonic
2025-02-19T00:19:56.759535image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 41824
91.0%
1 4151
 
9.0%
ValueCountFrequency (%)
0 41824
91.0%
1 4151
 
9.0%
ValueCountFrequency (%)
1 4151
 
9.0%
0 41824
91.0%
Distinct1843
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size3.1 MiB
2025-02-19T00:19:56.917869image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length44
Median length34
Mean length14.31253942
Min length5

Characters and Unicode

Total characters658019
Distinct characters69
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique702 ?
Unique (%)1.5%

Sample

1st rowunknown
2nd rowunknown
3rd row Kunitomo et al. 2011
4th row Liu et al. 2008
5th rowTeng et al. 2023
ValueCountFrequency (%)
al 13921
 
11.0%
et 13921
 
11.0%
table 13483
 
10.6%
koi 13483
 
10.6%
unknown 8316
 
6.6%
ticv8 7384
 
5.8%
q1-q17 5783
 
4.6%
2018 4338
 
3.4%
dr25 3084
 
2.4%
2016 2932
 
2.3%
Other values (945) 40043
31.6%
2025-02-19T00:19:57.091911image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
84998
 
12.9%
e 39459
 
6.0%
1 37669
 
5.7%
a 35988
 
5.5%
n 34082
 
5.2%
l 31259
 
4.8%
2 28236
 
4.3%
Q 26996
 
4.1%
T 23452
 
3.6%
t 22241
 
3.4%
Other values (59) 293639
44.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 658019
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
84998
 
12.9%
e 39459
 
6.0%
1 37669
 
5.7%
a 35988
 
5.5%
n 34082
 
5.2%
l 31259
 
4.8%
2 28236
 
4.3%
Q 26996
 
4.1%
T 23452
 
3.6%
t 22241
 
3.4%
Other values (59) 293639
44.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 658019
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
84998
 
12.9%
e 39459
 
6.0%
1 37669
 
5.7%
a 35988
 
5.5%
n 34082
 
5.2%
l 31259
 
4.8%
2 28236
 
4.3%
Q 26996
 
4.1%
T 23452
 
3.6%
t 22241
 
3.4%
Other values (59) 293639
44.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 658019
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
84998
 
12.9%
e 39459
 
6.0%
1 37669
 
5.7%
a 35988
 
5.5%
n 34082
 
5.2%
l 31259
 
4.8%
2 28236
 
4.3%
Q 26996
 
4.1%
T 23452
 
3.6%
t 22241
 
3.4%
Other values (59) 293639
44.6%

star_temperature_x
Real number (ℝ)

Distinct4394
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5501.55856
Minimum415
Maximum57000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:19:57.170917image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum415
5-th percentile3943
Q15295
median5614
Q35843.015
95-th percentile6299
Maximum57000
Range56585
Interquartile range (IQR)548.015

Descriptive statistics

Standard deviation867.8515931
Coefficient of variation (CV)0.1577464974
Kurtosis777.1554899
Mean5501.55856
Median Absolute Deviation (MAD)263
Skewness16.46782822
Sum252934154.8
Variance753166.3877
MonotonicityNot monotonic
2025-02-19T00:19:57.235104image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5614 10931
 
23.8%
5900 86
 
0.2%
5600 84
 
0.2%
5800 63
 
0.1%
5700 62
 
0.1%
6063 57
 
0.1%
6000 57
 
0.1%
5741 56
 
0.1%
5500 55
 
0.1%
6050 54
 
0.1%
Other values (4384) 34470
75.0%
ValueCountFrequency (%)
415 1
< 0.1%
575 1
< 0.1%
580.5 1
< 0.1%
2320 1
< 0.1%
2375 1
< 0.1%
ValueCountFrequency (%)
57000 2
< 0.1%
40000 1
 
< 0.1%
32780 4
< 0.1%
29564 3
< 0.1%
29300 1
 
< 0.1%

st_tefferr1
Real number (ℝ)

Skewed 

Distinct3287
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean115.3559569
Minimum0
Maximum6064.9
Zeros11
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:19:57.315167image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile49
Q191
median114
Q3130.42
95-th percentile184
Maximum6064.9
Range6064.9
Interquartile range (IQR)39.42

Descriptive statistics

Standard deviation64.10182003
Coefficient of variation (CV)0.5556871247
Kurtosis3080.478214
Mean115.3559569
Median Absolute Deviation (MAD)20.29
Skewness38.07171266
Sum5303490.12
Variance4109.043331
MonotonicityNot monotonic
2025-02-19T00:19:57.362442image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
114 11844
25.8%
122 2438
 
5.3%
60 1669
 
3.6%
100 1081
 
2.4%
50 756
 
1.6%
157 703
 
1.5%
123 583
 
1.3%
200 530
 
1.2%
75 373
 
0.8%
80 320
 
0.7%
Other values (3277) 25678
55.9%
ValueCountFrequency (%)
0 11
< 0.1%
1 1
 
< 0.1%
1.87 1
 
< 0.1%
3 4
 
< 0.1%
4 1
 
< 0.1%
ValueCountFrequency (%)
6064.9 1
 
< 0.1%
5084 1
 
< 0.1%
4879.8 1
 
< 0.1%
1388.8 1
 
< 0.1%
1067 7
< 0.1%

st_tefferr2
Real number (ℝ)

Skewed 

Distinct3349
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-117.6241473
Minimum-6064.9
Maximum0
Zeros22
Zeros (%)< 0.1%
Negative45953
Negative (%)> 99.9%
Memory size359.3 KiB
2025-02-19T00:19:57.439539image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-6064.9
5-th percentile-200
Q1-131
median-117
Q3-91
95-th percentile-48
Maximum0
Range6064.9
Interquartile range (IQR)40

Descriptive statistics

Standard deviation65.69753921
Coefficient of variation (CV)-0.5585378576
Kurtosis2809.276447
Mean-117.6241473
Median Absolute Deviation (MAD)19.41
Skewness-35.71018426
Sum-5407770.17
Variance4316.166659
MonotonicityNot monotonic
2025-02-19T00:19:57.519014image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-117 12201
26.5%
-122 2446
 
5.3%
-60 1674
 
3.6%
-100 986
 
2.1%
-50 768
 
1.7%
-123 604
 
1.3%
-200 571
 
1.2%
-157 525
 
1.1%
-75 360
 
0.8%
-80 277
 
0.6%
Other values (3339) 25563
55.6%
ValueCountFrequency (%)
-6064.9 1
< 0.1%
-5084 1
< 0.1%
-4879.8 1
< 0.1%
-2360.24 1
< 0.1%
-1388.8 1
< 0.1%
ValueCountFrequency (%)
0 22
< 0.1%
-1 1
 
< 0.1%
-1.51 1
 
< 0.1%
-3 4
 
< 0.1%
-4 1
 
< 0.1%

st_tefflim
Real number (ℝ)

Skewed  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.17509516 × 10-5
Minimum0
Maximum1
Zeros45974
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:19:57.579274image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.004663791548
Coefficient of variation (CV)214.4178164
Kurtosis45975
Mean2.17509516 × 10-5
Median Absolute Deviation (MAD)0
Skewness214.4178164
Sum1
Variance2.17509516 × 10-5
MonotonicityNot monotonic
2025-02-19T00:19:57.632726image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 45974
> 99.9%
1 1
 
< 0.1%
ValueCountFrequency (%)
0 45974
> 99.9%
1 1
 
< 0.1%
ValueCountFrequency (%)
1 1
 
< 0.1%
0 45974
> 99.9%

star_radius_x
Real number (ℝ)

Skewed 

Distinct589
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.104904622
Minimum0.01
Maximum88.47
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:19:57.783992image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.55
Q10.84
median0.95
Q31.1
95-th percentile1.74
Maximum88.47
Range88.46
Interquartile range (IQR)0.26

Descriptive statistics

Standard deviation1.569787269
Coefficient of variation (CV)1.420744594
Kurtosis1109.629819
Mean1.104904622
Median Absolute Deviation (MAD)0.13
Skewness28.37729697
Sum50797.99
Variance2.464232069
MonotonicityNot monotonic
2025-02-19T00:19:57.840507image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.95 11292
 
24.6%
0.83 611
 
1.3%
0.8 592
 
1.3%
0.85 592
 
1.3%
0.94 568
 
1.2%
0.86 568
 
1.2%
0.89 553
 
1.2%
0.81 549
 
1.2%
0.87 548
 
1.2%
0.77 548
 
1.2%
Other values (579) 29554
64.3%
ValueCountFrequency (%)
0.01 1
 
< 0.1%
0.09 1
 
< 0.1%
0.11 6
 
< 0.1%
0.12 34
0.1%
0.14 8
 
< 0.1%
ValueCountFrequency (%)
88.47 1
< 0.1%
86.4 1
< 0.1%
83.8 1
< 0.1%
71.23 1
< 0.1%
71.02 1
< 0.1%

st_raderr1
Real number (ℝ)

Skewed 

Distinct206
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1619934747
Minimum0
Maximum104.53
Zeros112
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:19:57.913980image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.02
Q10.06
median0.08
Q30.15
95-th percentile0.5
Maximum104.53
Range104.53
Interquartile range (IQR)0.09

Descriptive statistics

Standard deviation0.7095544339
Coefficient of variation (CV)4.380142071
Kurtosis12945.97196
Mean0.1619934747
Median Absolute Deviation (MAD)0.03
Skewness100.4102872
Sum7447.65
Variance0.5034674946
MonotonicityNot monotonic
2025-02-19T00:19:57.988827image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.08 17341
37.7%
0.02 2320
 
5.0%
0.03 2315
 
5.0%
0.04 2282
 
5.0%
0.05 2158
 
4.7%
0.06 1980
 
4.3%
0.07 1490
 
3.2%
0.01 1388
 
3.0%
0.09 685
 
1.5%
0.1 612
 
1.3%
Other values (196) 13404
29.2%
ValueCountFrequency (%)
0 112
 
0.2%
0.01 1388
3.0%
0.02 2320
5.0%
0.03 2315
5.0%
0.04 2282
5.0%
ValueCountFrequency (%)
104.53 1
< 0.1%
73.63 1
< 0.1%
35.82 1
< 0.1%
26 2
< 0.1%
22.81 1
< 0.1%

st_raderr2
Real number (ℝ)

Skewed 

Distinct182
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.1042001088
Minimum-73.63
Maximum0
Zeros127
Zeros (%)0.3%
Negative45848
Negative (%)99.7%
Memory size359.3 KiB
2025-02-19T00:19:58.058546image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-73.63
5-th percentile-0.35
Q1-0.08
median-0.06
Q3-0.05
95-th percentile-0.02
Maximum0
Range73.63
Interquartile range (IQR)0.03

Descriptive statistics

Standard deviation0.4925661402
Coefficient of variation (CV)-4.727117333
Kurtosis11947.8502
Mean-0.1042001088
Median Absolute Deviation (MAD)0.01
Skewness-93.17670228
Sum-4790.6
Variance0.2426214025
MonotonicityNot monotonic
2025-02-19T00:19:58.142167image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.06 19557
42.5%
-0.05 2707
 
5.9%
-0.04 2694
 
5.9%
-0.03 2515
 
5.5%
-0.07 2507
 
5.5%
-0.02 2412
 
5.2%
-0.08 1590
 
3.5%
-0.09 1421
 
3.1%
-0.01 1403
 
3.1%
-0.1 1078
 
2.3%
Other values (172) 8091
17.6%
ValueCountFrequency (%)
-73.63 1
< 0.1%
-35.82 1
< 0.1%
-26 2
< 0.1%
-22.81 1
< 0.1%
-18.22 1
< 0.1%
ValueCountFrequency (%)
0 127
 
0.3%
-0.01 1403
3.1%
-0.02 2412
5.2%
-0.03 2515
5.5%
-0.04 2694
5.9%

st_radlim
Real number (ℝ)

Skewed  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.350190321 × 10-5
Minimum0
Maximum1
Zeros45973
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:19:58.195137image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.006595525527
Coefficient of variation (CV)151.6146431
Kurtosis22984.99983
Mean4.350190321 × 10-5
Median Absolute Deviation (MAD)0
Skewness151.611345
Sum2
Variance4.350095698 × 10-5
MonotonicityNot monotonic
2025-02-19T00:19:58.239212image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 45973
> 99.9%
1 2
 
< 0.1%
ValueCountFrequency (%)
0 45973
> 99.9%
1 2
 
< 0.1%
ValueCountFrequency (%)
1 2
 
< 0.1%
0 45973
> 99.9%

star_mass_x
Real number (ℝ)

Distinct269
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.9502151169
Minimum0
Maximum23.56
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:19:58.303396image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.55
Q10.88
median0.96
Q31.02
95-th percentile1.26
Maximum23.56
Range23.56
Interquartile range (IQR)0.14

Descriptive statistics

Standard deviation0.2723947082
Coefficient of variation (CV)0.2866663593
Kurtosis1219.469005
Mean0.9502151169
Median Absolute Deviation (MAD)0.07
Skewness18.56107524
Sum43686.14
Variance0.07419887703
MonotonicityNot monotonic
2025-02-19T00:19:58.371651image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.96 14432
31.4%
1 870
 
1.9%
1.02 768
 
1.7%
1.01 747
 
1.6%
0.94 742
 
1.6%
0.98 729
 
1.6%
0.99 729
 
1.6%
0.97 717
 
1.6%
1.03 705
 
1.5%
0.95 696
 
1.5%
Other values (259) 24840
54.0%
ValueCountFrequency (%)
0 1
 
< 0.1%
0.01 4
 
< 0.1%
0.02 10
< 0.1%
0.03 5
< 0.1%
0.04 2
 
< 0.1%
ValueCountFrequency (%)
23.56 1
< 0.1%
10.94 1
< 0.1%
10.83 1
< 0.1%
9.9 1
< 0.1%
9.81 1
< 0.1%

st_masserr1
Real number (ℝ)

Skewed 

Distinct105
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.09073648722
Minimum0
Maximum97.1
Zeros73
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:19:58.431009image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.02
Q10.07
median0.07
Q30.09
95-th percentile0.22
Maximum97.1
Range97.1
Interquartile range (IQR)0.02

Descriptive statistics

Standard deviation0.4802113697
Coefficient of variation (CV)5.292373381
Kurtosis36372.49567
Mean0.09073648722
Median Absolute Deviation (MAD)0.01
Skewness182.7964386
Sum4171.61
Variance0.2306029596
MonotonicityNot monotonic
2025-02-19T00:19:58.507858image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.07 21154
46.0%
0.03 2516
 
5.5%
0.04 2261
 
4.9%
0.02 2003
 
4.4%
0.06 1987
 
4.3%
0.05 1781
 
3.9%
0.1 1554
 
3.4%
0.09 1283
 
2.8%
0.08 1279
 
2.8%
0.12 1177
 
2.6%
Other values (95) 8980
19.5%
ValueCountFrequency (%)
0 73
 
0.2%
0.01 828
 
1.8%
0.02 2003
4.4%
0.03 2516
5.5%
0.04 2261
4.9%
ValueCountFrequency (%)
97.1 1
< 0.1%
22.96 1
< 0.1%
16.45 1
< 0.1%
10.02 1
< 0.1%
4.21 1
< 0.1%

st_masserr2
Real number (ℝ)

Skewed 

Distinct102
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.08273300707
Minimum-97.1
Maximum0
Zeros67
Zeros (%)0.1%
Negative45908
Negative (%)99.9%
Memory size359.3 KiB
2025-02-19T00:19:58.590132image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-97.1
5-th percentile-0.16
Q1-0.08
median-0.07
Q3-0.06
95-th percentile-0.02
Maximum0
Range97.1
Interquartile range (IQR)0.02

Descriptive statistics

Standard deviation0.4785951926
Coefficient of variation (CV)-5.784815632
Kurtosis36878.64765
Mean-0.08273300707
Median Absolute Deviation (MAD)0.01
Skewness-184.6952829
Sum-3803.65
Variance0.2290533584
MonotonicityNot monotonic
2025-02-19T00:19:58.657977image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.07 21443
46.6%
-0.06 2694
 
5.9%
-0.03 2619
 
5.7%
-0.04 2363
 
5.1%
-0.05 2179
 
4.7%
-0.02 1865
 
4.1%
-0.09 1607
 
3.5%
-0.12 1540
 
3.3%
-0.08 1538
 
3.3%
-0.1 1423
 
3.1%
Other values (92) 6704
 
14.6%
ValueCountFrequency (%)
-97.1 1
< 0.1%
-22.96 1
< 0.1%
-16.45 1
< 0.1%
-10.02 1
< 0.1%
-4.21 1
< 0.1%
ValueCountFrequency (%)
0 67
 
0.1%
-0.01 782
 
1.7%
-0.02 1865
4.1%
-0.03 2619
5.7%
-0.04 2363
5.1%

st_masslim
Real number (ℝ)

Zeros 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-4.350190321 × 10-5
Minimum-1
Maximum1
Zeros45965
Zeros (%)> 99.9%
Negative6
Negative (%)< 0.1%
Memory size359.3 KiB
2025-02-19T00:19:58.718458image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range2
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.01474830006
Coefficient of variation (CV)-339.0265477
Kurtosis4594.919885
Mean-4.350190321 × 10-5
Median Absolute Deviation (MAD)0
Skewness-13.55274359
Sum-2
Variance0.0002175123547
MonotonicityNot monotonic
2025-02-19T00:19:58.763777image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=3)
ValueCountFrequency (%)
0 45965
> 99.9%
-1 6
 
< 0.1%
1 4
 
< 0.1%
ValueCountFrequency (%)
-1 6
 
< 0.1%
0 45965
> 99.9%
1 4
 
< 0.1%
ValueCountFrequency (%)
1 4
 
< 0.1%
0 45965
> 99.9%
-1 6
 
< 0.1%

st_met
Real number (ℝ)

Zeros 

Distinct757
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.016191441
Minimum-2.5
Maximum7.79
Zeros825
Zeros (%)1.8%
Negative33892
Negative (%)73.7%
Memory size359.3 KiB
2025-02-19T00:19:58.828496image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-2.5
5-th percentile-0.3
Q1-0.02
median-0.0085
Q30
95-th percentile0.248
Maximum7.79
Range10.29
Interquartile range (IQR)0.02

Descriptive statistics

Standard deviation0.1653789185
Coefficient of variation (CV)-10.2139716
Kurtosis117.124017
Mean-0.016191441
Median Absolute Deviation (MAD)0.0115
Skewness1.090195943
Sum-744.4015
Variance0.0273501867
MonotonicityNot monotonic
2025-02-19T00:19:58.991090image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.0085 21701
47.2%
0 825
 
1.8%
0.07 710
 
1.5%
-0.02 656
 
1.4%
-0.1 623
 
1.4%
-0.06 579
 
1.3%
-0.14 563
 
1.2%
0.02 560
 
1.2%
-0.2 556
 
1.2%
-0.08 545
 
1.2%
Other values (747) 18657
40.6%
ValueCountFrequency (%)
-2.5 3
< 0.1%
-1.7 4
< 0.1%
-1.46 4
< 0.1%
-1.44 3
< 0.1%
-1.42 4
< 0.1%
ValueCountFrequency (%)
7.79 1
 
< 0.1%
0.74 1
 
< 0.1%
0.56 54
0.1%
0.549 1
 
< 0.1%
0.545 2
 
< 0.1%

st_meterr1
Real number (ℝ)

Distinct246
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1362989886
Minimum0
Maximum0.96
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:19:59.057719image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.03
Q10.12
median0.129
Q30.135
95-th percentile0.3
Maximum0.96
Range0.96
Interquartile range (IQR)0.015

Descriptive statistics

Standard deviation0.07027322122
Coefficient of variation (CV)0.5155813844
Kurtosis3.013197928
Mean0.1362989886
Median Absolute Deviation (MAD)0.009
Skewness1.179454203
Sum6266.346
Variance0.004938325621
MonotonicityNot monotonic
2025-02-19T00:19:59.128677image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.129 22406
48.7%
0.15 2082
 
4.5%
0.04 1807
 
3.9%
0.1 1634
 
3.6%
0.3 1174
 
2.6%
0.08 887
 
1.9%
0.22 776
 
1.7%
0.24 720
 
1.6%
0.28 686
 
1.5%
0.2 651
 
1.4%
Other values (236) 13152
28.6%
ValueCountFrequency (%)
0 2
 
< 0.1%
0.001 1
 
< 0.1%
0.002 13
< 0.1%
0.003 1
 
< 0.1%
0.004 15
< 0.1%
ValueCountFrequency (%)
0.96 1
< 0.1%
0.95 1
< 0.1%
0.88 1
< 0.1%
0.625 1
< 0.1%
0.51 2
< 0.1%

st_meterr2
Real number (ℝ)

Distinct272
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.1474618162
Minimum-1
Maximum0
Zeros3
Zeros (%)< 0.1%
Negative45972
Negative (%)> 99.9%
Memory size359.3 KiB
2025-02-19T00:19:59.194722image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-0.3
Q1-0.148
median-0.14
Q3-0.14
95-th percentile-0.03
Maximum0
Range1
Interquartile range (IQR)0.008

Descriptive statistics

Standard deviation0.07561580123
Coefficient of variation (CV)-0.5127822454
Kurtosis1.814905983
Mean-0.1474618162
Median Absolute Deviation (MAD)0.004
Skewness-0.8894912792
Sum-6779.557
Variance0.005717749396
MonotonicityNot monotonic
2025-02-19T00:19:59.278143image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.14 22916
49.8%
-0.3 2747
 
6.0%
-0.15 1996
 
4.3%
-0.04 1787
 
3.9%
-0.1 1615
 
3.5%
-0.28 1536
 
3.3%
-0.26 1452
 
3.2%
-0.08 757
 
1.6%
-0.32 465
 
1.0%
-0.05 443
 
1.0%
Other values (262) 10261
22.3%
ValueCountFrequency (%)
-1 1
 
< 0.1%
-0.99 1
 
< 0.1%
-0.7 1
 
< 0.1%
-0.65 3
< 0.1%
-0.625 1
 
< 0.1%
ValueCountFrequency (%)
0 3
 
< 0.1%
-0.001 1
 
< 0.1%
-0.002 13
< 0.1%
-0.003 1
 
< 0.1%
-0.004 15
< 0.1%

st_metlim
Real number (ℝ)

Skewed  Zeros 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.0001305057096
Minimum-1
Maximum1
Zeros45967
Zeros (%)> 99.9%
Negative7
Negative (%)< 0.1%
Memory size359.3 KiB
2025-02-19T00:19:59.365793image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range2
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.01319069239
Coefficient of variation (CV)-101.0736804
Kurtosis5743.375043
Mean-0.0001305057096
Median Absolute Deviation (MAD)0
Skewness-56.83662986
Sum-6
Variance0.0001739943656
MonotonicityNot monotonic
2025-02-19T00:19:59.405695image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=3)
ValueCountFrequency (%)
0 45967
> 99.9%
-1 7
 
< 0.1%
1 1
 
< 0.1%
ValueCountFrequency (%)
-1 7
 
< 0.1%
0 45967
> 99.9%
1 1
 
< 0.1%
ValueCountFrequency (%)
1 1
 
< 0.1%
0 45967
> 99.9%
-1 7
 
< 0.1%
Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.8 MiB
2025-02-19T00:19:59.459685image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.390125068
Min length5

Characters and Unicode

Total characters293786
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowunknown
2nd rowunknown
3rd rowunknown
4th row[Fe/H]
5th row[Fe/H]
ValueCountFrequency (%)
unknown 21898
47.6%
fe/h 20115
43.8%
m/h 3962
 
8.6%
2025-02-19T00:19:59.572793image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 65694
22.4%
H 24077
 
8.2%
] 24077
 
8.2%
/ 24077
 
8.2%
[ 24077
 
8.2%
w 21898
 
7.5%
o 21898
 
7.5%
k 21898
 
7.5%
u 21898
 
7.5%
e 20115
 
6.8%
Other values (3) 24077
 
8.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 293786
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 65694
22.4%
H 24077
 
8.2%
] 24077
 
8.2%
/ 24077
 
8.2%
[ 24077
 
8.2%
w 21898
 
7.5%
o 21898
 
7.5%
k 21898
 
7.5%
u 21898
 
7.5%
e 20115
 
6.8%
Other values (3) 24077
 
8.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 293786
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 65694
22.4%
H 24077
 
8.2%
] 24077
 
8.2%
/ 24077
 
8.2%
[ 24077
 
8.2%
w 21898
 
7.5%
o 21898
 
7.5%
k 21898
 
7.5%
u 21898
 
7.5%
e 20115
 
6.8%
Other values (3) 24077
 
8.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 293786
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 65694
22.4%
H 24077
 
8.2%
] 24077
 
8.2%
/ 24077
 
8.2%
[ 24077
 
8.2%
w 21898
 
7.5%
o 21898
 
7.5%
k 21898
 
7.5%
u 21898
 
7.5%
e 20115
 
6.8%
Other values (3) 24077
 
8.2%

st_logg
Real number (ℝ)

Distinct317
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.431755954
Minimum0.1
Maximum7.92
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:19:59.620820image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile4.06
Q14.41
median4.47
Q34.51
95-th percentile4.69
Maximum7.92
Range7.82
Interquartile range (IQR)0.1

Descriptive statistics

Standard deviation0.2403445826
Coefficient of variation (CV)0.0542323596
Kurtosis39.23957619
Mean4.431755954
Median Absolute Deviation (MAD)0.05
Skewness-4.176773576
Sum203749.98
Variance0.05776551838
MonotonicityNot monotonic
2025-02-19T00:19:59.693532image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.47 16985
36.9%
4.54 859
 
1.9%
4.5 855
 
1.9%
4.49 791
 
1.7%
4.56 768
 
1.7%
4.51 767
 
1.7%
4.58 749
 
1.6%
4.55 726
 
1.6%
4.57 693
 
1.5%
4.52 687
 
1.5%
Other values (307) 22095
48.1%
ValueCountFrequency (%)
0.1 1
< 0.1%
0.54 1
< 0.1%
0.8 1
< 0.1%
0.9 1
< 0.1%
1.1 2
< 0.1%
ValueCountFrequency (%)
7.92 1
 
< 0.1%
5.74 4
< 0.1%
5.52 2
< 0.1%
5.51 3
< 0.1%
5.4 3
< 0.1%

st_loggerr1
Real number (ℝ)

Distinct83
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0859245242
Minimum0
Maximum2.01
Zeros119
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:19:59.770536image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.02
Q10.06
median0.07
Q30.07
95-th percentile0.3
Maximum2.01
Range2.01
Interquartile range (IQR)0.01

Descriptive statistics

Standard deviation0.0820456523
Coefficient of variation (CV)0.9548572199
Kurtosis125.56483
Mean0.0859245242
Median Absolute Deviation (MAD)0
Skewness7.36953329
Sum3950.38
Variance0.006731489061
MonotonicityNot monotonic
2025-02-19T00:19:59.840822image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.07 23166
50.4%
0.03 3113
 
6.8%
0.3 2277
 
5.0%
0.04 2070
 
4.5%
0.05 1754
 
3.8%
0.1 1683
 
3.7%
0.06 1611
 
3.5%
0.08 1577
 
3.4%
0.02 1566
 
3.4%
0.01 1521
 
3.3%
Other values (73) 5637
 
12.3%
ValueCountFrequency (%)
0 119
 
0.3%
0.01 1521
3.3%
0.02 1566
3.4%
0.03 3113
6.8%
0.04 2070
4.5%
ValueCountFrequency (%)
2.01 2
 
< 0.1%
2 14
< 0.1%
1.96 1
 
< 0.1%
1.75 1
 
< 0.1%
1.62 1
 
< 0.1%

st_loggerr2
Real number (ℝ)

Distinct102
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.1342309951
Minimum-3.51
Maximum0
Zeros121
Zeros (%)0.3%
Negative45854
Negative (%)99.7%
Memory size359.3 KiB
2025-02-19T00:19:59.910589image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-3.51
5-th percentile-0.3
Q1-0.12
median-0.11
Q3-0.1
95-th percentile-0.02
Maximum0
Range3.51
Interquartile range (IQR)0.02

Descriptive statistics

Standard deviation0.1038913119
Coefficient of variation (CV)-0.7739740869
Kurtosis83.3859551
Mean-0.1342309951
Median Absolute Deviation (MAD)0.01
Skewness-5.41974
Sum-6171.27
Variance0.01079340468
MonotonicityNot monotonic
2025-02-19T00:19:59.974185image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.11 22337
48.6%
-0.3 2900
 
6.3%
-0.1 1855
 
4.0%
-0.03 1344
 
2.9%
-0.08 1289
 
2.8%
-0.01 1277
 
2.8%
-0.02 1183
 
2.6%
-0.07 1100
 
2.4%
-0.09 989
 
2.2%
-0.04 980
 
2.1%
Other values (92) 10721
23.3%
ValueCountFrequency (%)
-3.51 1
 
< 0.1%
-2.86 1
 
< 0.1%
-2.01 2
 
< 0.1%
-2 14
< 0.1%
-1.96 1
 
< 0.1%
ValueCountFrequency (%)
0 121
 
0.3%
-0.01 1277
2.8%
-0.02 1183
2.6%
-0.03 1344
2.9%
-0.04 980
2.1%

st_logglim
Real number (ℝ)

Skewed  Zeros 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.0001305057096
Minimum-1
Maximum1
Zeros45967
Zeros (%)> 99.9%
Negative7
Negative (%)< 0.1%
Memory size359.3 KiB
2025-02-19T00:20:00.035740image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range2
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.01319069239
Coefficient of variation (CV)-101.0736804
Kurtosis5743.375043
Mean-0.0001305057096
Median Absolute Deviation (MAD)0
Skewness-56.83662986
Sum-6
Variance0.0001739943656
MonotonicityNot monotonic
2025-02-19T00:20:00.069320image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=3)
ValueCountFrequency (%)
0 45967
> 99.9%
-1 7
 
< 0.1%
1 1
 
< 0.1%
ValueCountFrequency (%)
-1 7
 
< 0.1%
0 45967
> 99.9%
1 1
 
< 0.1%
ValueCountFrequency (%)
1 1
 
< 0.1%
0 45967
> 99.9%
-1 7
 
< 0.1%
Distinct152
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.7 MiB
2025-02-19T00:20:00.255044image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length33
Median length5
Mean length5.525568244
Min length5

Characters and Unicode

Total characters254038
Distinct characters61
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)0.1%

Sample

1st rowunknown
2nd rowunknown
3rd rowTICv8
4th rowTICv8
5th rowTICv8
ValueCountFrequency (%)
ticv8 37334
77.8%
unknown 7966
 
16.6%
et 661
 
1.4%
al 661
 
1.4%
2022 156
 
0.3%
han 147
 
0.3%
2023 82
 
0.2%
2024 72
 
0.1%
2020 58
 
0.1%
ryu 56
 
0.1%
Other values (98) 814
 
1.7%
2025-02-19T00:20:00.429284image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 37391
14.7%
v 37350
14.7%
C 37346
14.7%
T 37341
14.7%
I 37336
14.7%
n 24366
9.6%
u 8166
 
3.2%
o 8131
 
3.2%
k 8037
 
3.2%
w 8000
 
3.1%
Other values (51) 10574
 
4.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 254038
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
8 37391
14.7%
v 37350
14.7%
C 37346
14.7%
T 37341
14.7%
I 37336
14.7%
n 24366
9.6%
u 8166
 
3.2%
o 8131
 
3.2%
k 8037
 
3.2%
w 8000
 
3.1%
Other values (51) 10574
 
4.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 254038
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
8 37391
14.7%
v 37350
14.7%
C 37346
14.7%
T 37341
14.7%
I 37336
14.7%
n 24366
9.6%
u 8166
 
3.2%
o 8131
 
3.2%
k 8037
 
3.2%
w 8000
 
3.1%
Other values (51) 10574
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 254038
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
8 37391
14.7%
v 37350
14.7%
C 37346
14.7%
T 37341
14.7%
I 37336
14.7%
n 24366
9.6%
u 8166
 
3.2%
o 8131
 
3.2%
k 8037
 
3.2%
w 8000
 
3.1%
Other values (51) 10574
 
4.2%

rastr
Text

Distinct4349
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size3.0 MiB
2025-02-19T00:20:00.509400image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length14
Median length12
Mean length11.13320283
Min length7

Characters and Unicode

Total characters511849
Distinct characters19
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique469 ?
Unique (%)1.0%

Sample

1st rowunknown
2nd rowunknown
3rd row12h20m42.91s
4th row12h20m42.91s
5th row12h20m42.91s
ValueCountFrequency (%)
unknown 7966
 
17.3%
19h48m27.62s 97
 
0.2%
19h44m27.02s 83
 
0.2%
18h57m44.03s 77
 
0.2%
19h51m22.15s 76
 
0.2%
19h10m47.52s 76
 
0.2%
19h54m36.66s 75
 
0.2%
18h45m55.79s 73
 
0.2%
19h06m09.61s 69
 
0.2%
19h16m18.61s 67
 
0.1%
Other values (4339) 37316
81.2%
2025-02-19T00:20:00.683088image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 60115
11.7%
9 40944
 
8.0%
m 38009
 
7.4%
s 38009
 
7.4%
. 38009
 
7.4%
h 38009
 
7.4%
0 32448
 
6.3%
2 31778
 
6.2%
4 28954
 
5.7%
5 28947
 
5.7%
Other values (9) 136627
26.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 511849
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 60115
11.7%
9 40944
 
8.0%
m 38009
 
7.4%
s 38009
 
7.4%
. 38009
 
7.4%
h 38009
 
7.4%
0 32448
 
6.3%
2 31778
 
6.2%
4 28954
 
5.7%
5 28947
 
5.7%
Other values (9) 136627
26.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 511849
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 60115
11.7%
9 40944
 
8.0%
m 38009
 
7.4%
s 38009
 
7.4%
. 38009
 
7.4%
h 38009
 
7.4%
0 32448
 
6.3%
2 31778
 
6.2%
4 28954
 
5.7%
5 28947
 
5.7%
Other values (9) 136627
26.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 511849
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 60115
11.7%
9 40944
 
8.0%
m 38009
 
7.4%
s 38009
 
7.4%
. 38009
 
7.4%
h 38009
 
7.4%
0 32448
 
6.3%
2 31778
 
6.2%
4 28954
 
5.7%
5 28947
 
5.7%
Other values (9) 136627
26.7%

ra_x
Real number (ℝ)

Distinct4357
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean268.4257381
Minimum0.1856063
Maximum359.9749837
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:20:00.795129image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.1856063
5-th percentile97.7487104
Q1285.146622
median289.6785786
Q3293.4548441
95-th percentile299.2216728
Maximum359.9749837
Range359.7893774
Interquartile range (IQR)8.3082221

Descriptive statistics

Standard deviation63.69968068
Coefficient of variation (CV)0.2373083935
Kurtosis5.999696853
Mean268.4257381
Median Absolute Deviation (MAD)4.1378802
Skewness-2.598511282
Sum12340873.31
Variance4057.649318
MonotonicityNot monotonic
2025-02-19T00:20:00.932440image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
289.6785786 7974
 
17.3%
297.1150949 97
 
0.2%
296.1125759 83
 
0.2%
284.4334642 77
 
0.2%
287.6979913 76
 
0.2%
297.8423073 76
 
0.2%
298.652736 75
 
0.2%
281.4824731 73
 
0.2%
286.5400278 69
 
0.2%
289.0775348 67
 
0.1%
Other values (4347) 37308
81.1%
ValueCountFrequency (%)
0.1856063 4
< 0.1%
0.325761 6
< 0.1%
0.3620995 7
< 0.1%
0.7744866 4
< 0.1%
1.0465696 7
< 0.1%
ValueCountFrequency (%)
359.9749837 2
 
< 0.1%
359.9008737 11
< 0.1%
359.7933851 3
 
< 0.1%
359.7164302 3
 
< 0.1%
359.3490277 14
< 0.1%

decstr
Text

Distinct4357
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size3.0 MiB
2025-02-19T00:20:01.110028image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length14
Median length13
Mean length11.95301794
Min length7

Characters and Unicode

Total characters549540
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique474 ?
Unique (%)1.0%

Sample

1st rowunknown
2nd rowunknown
3rd row+17d47m35.71s
4th row+17d47m35.71s
5th row+17d47m35.71s
ValueCountFrequency (%)
unknown 7966
 
17.3%
41d54m32.79s 97
 
0.2%
39d58m43.48s 83
 
0.2%
49d18m18.45s 77
 
0.2%
42d20m18.88s 76
 
0.2%
46d34m27.69s 76
 
0.2%
43d57m17.96s 75
 
0.2%
47d12m28.17s 73
 
0.2%
49d26m14.14s 69
 
0.2%
46d00m18.61s 67
 
0.1%
Other values (4347) 37316
81.2%
2025-02-19T00:20:01.273295image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 55919
 
10.2%
s 38009
 
6.9%
m 38009
 
6.9%
d 38009
 
6.9%
. 37988
 
6.9%
3 36188
 
6.6%
1 33868
 
6.2%
2 33719
 
6.1%
0 33361
 
6.1%
5 33246
 
6.0%
Other values (11) 171224
31.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 549540
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
4 55919
 
10.2%
s 38009
 
6.9%
m 38009
 
6.9%
d 38009
 
6.9%
. 37988
 
6.9%
3 36188
 
6.6%
1 33868
 
6.2%
2 33719
 
6.1%
0 33361
 
6.1%
5 33246
 
6.0%
Other values (11) 171224
31.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 549540
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
4 55919
 
10.2%
s 38009
 
6.9%
m 38009
 
6.9%
d 38009
 
6.9%
. 37988
 
6.9%
3 36188
 
6.6%
1 33868
 
6.2%
2 33719
 
6.1%
0 33361
 
6.1%
5 33246
 
6.0%
Other values (11) 171224
31.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 549540
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
4 55919
 
10.2%
s 38009
 
6.9%
m 38009
 
6.9%
d 38009
 
6.9%
. 37988
 
6.9%
3 36188
 
6.6%
1 33868
 
6.2%
2 33719
 
6.1%
0 33361
 
6.1%
5 33246
 
6.0%
Other values (11) 171224
31.2%

dec_x
Real number (ℝ)

Distinct4353
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.25957795
Minimum-88.1211107
Maximum86.860343
Zeros0
Zeros (%)0.0%
Negative5197
Negative (%)11.3%
Memory size359.3 KiB
2025-02-19T00:20:01.352093image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-88.1211107
5-th percentile-29.1019694
Q139.5234131
median42.6658336
Q345.9682799
95-th percentile49.9621218
Maximum86.860343
Range174.9814537
Interquartile range (IQR)6.4448668

Descriptive statistics

Standard deviation25.1044197
Coefficient of variation (CV)0.7327708396
Kurtosis5.054210274
Mean34.25957795
Median Absolute Deviation (MAD)3.2041246
Skewness-2.359986346
Sum1575084.096
Variance630.2318883
MonotonicityNot monotonic
2025-02-19T00:20:01.441445image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42.6658336 7976
 
17.3%
41.9091092 97
 
0.2%
39.9787451 83
 
0.2%
49.3051239 77
 
0.2%
46.5743595 76
 
0.2%
42.3385782 76
 
0.2%
43.9549884 75
 
0.2%
47.2078263 73
 
0.2%
49.4372614 69
 
0.2%
46.0051696 67
 
0.1%
Other values (4343) 37306
81.1%
ValueCountFrequency (%)
-88.1211107 2
< 0.1%
-86.979965 2
< 0.1%
-84.2317494 3
< 0.1%
-83.7437671 4
< 0.1%
-83.1297264 4
< 0.1%
ValueCountFrequency (%)
86.860343 3
< 0.1%
85.7365329 2
 
< 0.1%
85.2333208 6
< 0.1%
85.1294952 3
< 0.1%
84.3642652 2
 
< 0.1%

sy_dist
Real number (ℝ)

Distinct4338
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean701.0592079
Minimum1.30119
Maximum8800
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:20:01.511425image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1.30119
5-th percentile48.3016
Q1349.549
median595.683
Q3854.28
95-th percentile1530.32
Maximum8800
Range8798.69881
Interquartile range (IQR)504.731

Descriptive statistics

Standard deviation708.5742961
Coefficient of variation (CV)1.01071962
Kurtosis41.61961878
Mean701.0592079
Median Absolute Deviation (MAD)252.571
Skewness5.348576545
Sum32231197.08
Variance502077.5331
MonotonicityNot monotonic
2025-02-19T00:20:01.580939image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
595.683 8819
 
19.2%
646.346 97
 
0.2%
369.451 83
 
0.2%
848.254 77
 
0.2%
282.563 76
 
0.2%
323.847 76
 
0.2%
177.594 75
 
0.2%
107.796 73
 
0.2%
1209.16 67
 
0.1%
300.874 63
 
0.1%
Other values (4328) 36469
79.3%
ValueCountFrequency (%)
1.30119 4
< 0.1%
1.82655 1
 
< 0.1%
3.2026 5
< 0.1%
3.29 2
 
< 0.1%
3.37454 1
 
< 0.1%
ValueCountFrequency (%)
8800 1
 
< 0.1%
8600 1
 
< 0.1%
8300 1
 
< 0.1%
8240 4
< 0.1%
8200 1
 
< 0.1%

sy_disterr1
Real number (ℝ)

Distinct3823
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.91197304
Minimum0.00034
Maximum3160
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:20:01.659866image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.00034
5-th percentile0.10815
Q13.2515
median7.94
Q316.452
95-th percentile73.32
Maximum3160
Range3159.99966
Interquartile range (IQR)13.2005

Descriptive statistics

Standard deviation128.4835553
Coefficient of variation (CV)4.443956666
Kurtosis115.629237
Mean28.91197304
Median Absolute Deviation (MAD)5.534
Skewness10.0564846
Sum1329227.961
Variance16508.02399
MonotonicityNot monotonic
2025-02-19T00:20:01.757825image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.94 9656
 
21.0%
6.375 97
 
0.2%
16.92 85
 
0.2%
2.8945 83
 
0.2%
10.8185 77
 
0.2%
5 77
 
0.2%
3.4025 76
 
0.2%
1.776 76
 
0.2%
0.774 75
 
0.2%
6.7435 73
 
0.2%
Other values (3813) 35600
77.4%
ValueCountFrequency (%)
0.00034 4
< 0.1%
0.00041 1
 
< 0.1%
0.00055 4
< 0.1%
0.00068 5
< 0.1%
0.000805 1
 
< 0.1%
ValueCountFrequency (%)
3160 1
< 0.1%
2450 2
< 0.1%
2440 1
< 0.1%
2240 1
< 0.1%
2220 1
< 0.1%

sy_disterr2
Real number (ℝ)

Distinct3863
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-29.80639845
Minimum-2900
Maximum2700
Zeros0
Zeros (%)0.0%
Negative45970
Negative (%)> 99.9%
Memory size359.3 KiB
2025-02-19T00:20:01.862723image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-2900
5-th percentile-67.61
Q1-16.038
median-7.7825
Q3-3.198
95-th percentile-0.10815
Maximum2700
Range5600
Interquartile range (IQR)12.84

Descriptive statistics

Standard deviation150.1112999
Coefficient of variation (CV)-5.036210603
Kurtosis128.5807987
Mean-29.80639845
Median Absolute Deviation (MAD)5.4115
Skewness-10.05735563
Sum-1370349.169
Variance22533.40237
MonotonicityNot monotonic
2025-02-19T00:20:01.913917image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-7.7825 9637
 
21.0%
-6.375 97
 
0.2%
-18.64 84
 
0.2%
-2.8945 83
 
0.2%
-10.8185 77
 
0.2%
-3.4025 76
 
0.2%
-1.753 76
 
0.2%
-0.774 75
 
0.2%
-42.19 75
 
0.2%
-0.219 73
 
0.2%
Other values (3853) 35622
77.5%
ValueCountFrequency (%)
-2900 1
 
< 0.1%
-2840 1
 
< 0.1%
-2800 1
 
< 0.1%
-2700 2
< 0.1%
-2600 3
< 0.1%
ValueCountFrequency (%)
2700 1
< 0.1%
2600 1
< 0.1%
2200 1
< 0.1%
390 1
< 0.1%
60 1
< 0.1%

sy_vmag
Real number (ℝ)

Distinct3103
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.70279688
Minimum0.872
Maximum45.34
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:20:01.987805image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.872
5-th percentile8.87
Q113.061
median14.166
Q315.052
95-th percentile16.012
Maximum45.34
Range44.468
Interquartile range (IQR)1.991

Descriptive statistics

Standard deviation2.172937542
Coefficient of variation (CV)0.1585762061
Kurtosis6.965580364
Mean13.70279688
Median Absolute Deviation (MAD)0.968
Skewness-1.338131394
Sum629986.0864
Variance4.721657562
MonotonicityNot monotonic
2025-02-19T00:20:02.065190image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14.166 8695
 
18.9%
14.379 109
 
0.2%
13.965 97
 
0.2%
13.817 97
 
0.2%
15.138 85
 
0.2%
15.23 83
 
0.2%
13.883 77
 
0.2%
15.161 77
 
0.2%
16.36 76
 
0.2%
12.61 76
 
0.2%
Other values (3093) 36503
79.4%
ValueCountFrequency (%)
0.872 1
 
< 0.1%
1.12512 4
< 0.1%
1.99509 1
 
< 0.1%
2.00538 1
 
< 0.1%
2.0569 1
 
< 0.1%
ValueCountFrequency (%)
45.34 1
< 0.1%
44.61 1
< 0.1%
43.94 1
< 0.1%
41.62 1
< 0.1%
34.1 1
< 0.1%

sy_vmagerr1
Real number (ℝ)

Distinct193
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1119683154
Minimum0.001
Maximum11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:20:02.203164image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.001
5-th percentile0.015
Q10.069
median0.092
Q30.126
95-th percentile0.252
Maximum11
Range10.999
Interquartile range (IQR)0.057

Descriptive statistics

Standard deviation0.1353534598
Coefficient of variation (CV)1.208855017
Kurtosis1016.371961
Mean0.1119683154
Median Absolute Deviation (MAD)0.034
Skewness17.74200919
Sum5147.7433
Variance0.01832055908
MonotonicityNot monotonic
2025-02-19T00:20:02.250936image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.092 11757
25.6%
0.08 2952
 
6.4%
0.069 2663
 
5.8%
0.103 2408
 
5.2%
0.126 2142
 
4.7%
0.03 2012
 
4.4%
0.114 1561
 
3.4%
0.057 1460
 
3.2%
0.137 1374
 
3.0%
0.149 1260
 
2.7%
Other values (183) 16386
35.6%
ValueCountFrequency (%)
0.001 11
 
< 0.1%
0.002 94
 
0.2%
0.003 204
0.4%
0.004 303
0.7%
0.005 198
0.4%
ValueCountFrequency (%)
11 1
< 0.1%
5.2 1
< 0.1%
4.35 1
< 0.1%
3.35 1
< 0.1%
3.1 1
< 0.1%

sy_vmagerr2
Real number (ℝ)

Skewed 

Distinct192
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.1124575378
Minimum-12.27
Maximum-0.001
Zeros0
Zeros (%)0.0%
Negative45975
Negative (%)100.0%
Memory size359.3 KiB
2025-02-19T00:20:02.318263image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-12.27
5-th percentile-0.252
Q1-0.126
median-0.092
Q3-0.069
95-th percentile-0.015
Maximum-0.001
Range12.269
Interquartile range (IQR)0.057

Descriptive statistics

Standard deviation0.162343577
Coefficient of variation (CV)-1.443598893
Kurtosis2351.39228
Mean-0.1124575378
Median Absolute Deviation (MAD)0.034
Skewness-34.85153344
Sum-5170.2353
Variance0.026355437
MonotonicityNot monotonic
2025-02-19T00:20:02.380816image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.092 11758
25.6%
-0.08 2952
 
6.4%
-0.069 2663
 
5.8%
-0.103 2408
 
5.2%
-0.126 2142
 
4.7%
-0.03 2012
 
4.4%
-0.114 1561
 
3.4%
-0.057 1460
 
3.2%
-0.137 1374
 
3.0%
-0.149 1260
 
2.7%
Other values (182) 16385
35.6%
ValueCountFrequency (%)
-12.27 1
< 0.1%
-11.92 1
< 0.1%
-11.6 1
< 0.1%
-11.35 1
< 0.1%
-2.95 1
< 0.1%
ValueCountFrequency (%)
-0.001 11
 
< 0.1%
-0.002 94
 
0.2%
-0.003 204
0.4%
-0.004 303
0.7%
-0.005 198
0.4%

sy_kmag
Real number (ℝ)

Distinct3276
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.71036429
Minimum-3.044
Maximum35.33
Zeros0
Zeros (%)0.0%
Negative10
Negative (%)< 0.1%
Memory size359.3 KiB
2025-02-19T00:20:02.442256image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-3.044
5-th percentile6.763
Q111.203
median12.264
Q312.935
95-th percentile13.841
Maximum35.33
Range38.374
Interquartile range (IQR)1.732

Descriptive statistics

Standard deviation2.093962637
Coefficient of variation (CV)0.1788127667
Kurtosis5.079020915
Mean11.71036429
Median Absolute Deviation (MAD)0.809
Skewness-1.745655047
Sum538383.9981
Variance4.384679524
MonotonicityNot monotonic
2025-02-19T00:20:02.489547image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12.264 8676
 
18.9%
12.826 110
 
0.2%
12.383 103
 
0.2%
13.633 99
 
0.2%
12.18 97
 
0.2%
13.512 94
 
0.2%
11.966 89
 
0.2%
12.482 88
 
0.2%
10.871 85
 
0.2%
12.253 83
 
0.2%
Other values (3266) 36451
79.3%
ValueCountFrequency (%)
-3.044 1
 
< 0.1%
-1.846 1
 
< 0.1%
-1.287 1
 
< 0.1%
-1.189 1
 
< 0.1%
-0.936 4
< 0.1%
ValueCountFrequency (%)
35.33 1
< 0.1%
33.11 1
< 0.1%
31.09 1
< 0.1%
28.29 1
< 0.1%
25.5 1
< 0.1%

sy_kmagerr1
Real number (ℝ)

Skewed 

Distinct164
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.03341222403
Minimum0.011
Maximum9.995
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:20:02.594421image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.011
5-th percentile0.016
Q10.021
median0.024
Q30.031
95-th percentile0.054
Maximum9.995
Range9.984
Interquartile range (IQR)0.01

Descriptive statistics

Standard deviation0.1808941226
Coefficient of variation (CV)5.414010226
Kurtosis2405.157495
Mean0.03341222403
Median Absolute Deviation (MAD)0.004
Skewness47.81472403
Sum1536.127
Variance0.03272268359
MonotonicityNot monotonic
2025-02-19T00:20:02.641967image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.024 10721
23.3%
0.021 3241
 
7.0%
0.023 2730
 
5.9%
0.02 2354
 
5.1%
0.018 2192
 
4.8%
0.019 1841
 
4.0%
0.026 1546
 
3.4%
0.022 1266
 
2.8%
0.017 1241
 
2.7%
0.016 1145
 
2.5%
Other values (154) 17698
38.5%
ValueCountFrequency (%)
0.011 607
1.3%
0.012 112
 
0.2%
0.013 383
0.8%
0.014 435
0.9%
0.015 134
 
0.3%
ValueCountFrequency (%)
9.995 7
< 0.1%
8.888 4
< 0.1%
8.6 1
 
< 0.1%
8.14 1
 
< 0.1%
8.07 1
 
< 0.1%

sy_kmagerr2
Real number (ℝ)

Skewed 

Distinct162
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.03301461664
Minimum-11.14
Maximum-0.011
Zeros0
Zeros (%)0.0%
Negative45975
Negative (%)100.0%
Memory size359.3 KiB
2025-02-19T00:20:02.709649image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-11.14
5-th percentile-0.054
Q1-0.031
median-0.024
Q3-0.021
95-th percentile-0.016
Maximum-0.011
Range11.129
Interquartile range (IQR)0.01

Descriptive statistics

Standard deviation0.1736121119
Coefficient of variation (CV)-5.258643885
Kurtosis2902.180216
Mean-0.03301461664
Median Absolute Deviation (MAD)0.004
Skewness-52.50056348
Sum-1517.847
Variance0.0301411654
MonotonicityNot monotonic
2025-02-19T00:20:02.753192image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.024 10721
23.3%
-0.021 3241
 
7.0%
-0.023 2730
 
5.9%
-0.02 2354
 
5.1%
-0.018 2192
 
4.8%
-0.019 1841
 
4.0%
-0.026 1546
 
3.4%
-0.022 1266
 
2.8%
-0.017 1241
 
2.7%
-0.016 1145
 
2.5%
Other values (152) 17698
38.5%
ValueCountFrequency (%)
-11.14 1
 
< 0.1%
-9.995 7
< 0.1%
-9.4 1
 
< 0.1%
-8.888 4
< 0.1%
-7.82 1
 
< 0.1%
ValueCountFrequency (%)
-0.011 607
1.3%
-0.012 112
 
0.2%
-0.013 383
0.8%
-0.014 435
0.9%
-0.015 134
 
0.3%

sy_gaiamag
Real number (ℝ)

Distinct3970
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.48846509
Minimum2.36431
Maximum20.1861
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:20:02.837646image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum2.36431
5-th percentile8.643251
Q112.89795
median14.0004
Q314.8213
95-th percentile15.7753
Maximum20.1861
Range17.82179
Interquartile range (IQR)1.92335

Descriptive statistics

Standard deviation2.114086444
Coefficient of variation (CV)0.1567329143
Kurtosis3.609663842
Mean13.48846509
Median Absolute Deviation (MAD)0.9188
Skewness-1.787255865
Sum620132.1825
Variance4.469361491
MonotonicityNot monotonic
2025-02-19T00:20:02.896292image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14.0004 8994
 
19.6%
13.7062 97
 
0.2%
14.7555 83
 
0.2%
13.7397 77
 
0.2%
12.4535 76
 
0.2%
15.8123 76
 
0.2%
14.5994 75
 
0.2%
11.4784 73
 
0.2%
15.9015 69
 
0.2%
13.9513 67
 
0.1%
Other values (3960) 36288
78.9%
ValueCountFrequency (%)
2.36431 1
 
< 0.1%
2.92627 5
< 0.1%
2.96828 5
< 0.1%
3.04628 1
 
< 0.1%
3.09653 6
< 0.1%
ValueCountFrequency (%)
20.1861 1
 
< 0.1%
18.9668 1
 
< 0.1%
18.912 3
< 0.1%
18.765 1
 
< 0.1%
18.6333 2
< 0.1%

sy_gaiamagerr1
Real number (ℝ)

Skewed 

Distinct1102
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0004862507297
Minimum0.000118
Maximum0.063232
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:20:02.960162image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.000118
5-th percentile0.0001947
Q10.000271
median0.000352
Q30.000461
95-th percentile0.000917
Maximum0.063232
Range0.063114
Interquartile range (IQR)0.00019

Descriptive statistics

Standard deviation0.0009768478684
Coefficient of variation (CV)2.008938617
Kurtosis968.6714413
Mean0.0004862507297
Median Absolute Deviation (MAD)9 × 10-5
Skewness22.74225641
Sum22.3553773
Variance9.542317579 × 10-7
MonotonicityNot monotonic
2025-02-19T00:20:03.033909image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.000352 9024
 
19.6%
0.000273 292
 
0.6%
0.000236 260
 
0.6%
0.000254 232
 
0.5%
0.000249 209
 
0.5%
0.000253 208
 
0.5%
0.000208 199
 
0.4%
0.000201 191
 
0.4%
0.000268 191
 
0.4%
0.000217 186
 
0.4%
Other values (1092) 34983
76.1%
ValueCountFrequency (%)
0.000118 2
 
< 0.1%
0.000122 5
< 0.1%
0.000127 2
 
< 0.1%
0.000129 7
< 0.1%
0.000135 4
< 0.1%
ValueCountFrequency (%)
0.063232 2
 
< 0.1%
0.039434 2
 
< 0.1%
0.020612 4
< 0.1%
0.017417 8
< 0.1%
0.017262 7
< 0.1%

sy_gaiamagerr2
Real number (ℝ)

Skewed 

Distinct1102
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.0004862507297
Minimum-0.063232
Maximum-0.000118
Zeros0
Zeros (%)0.0%
Negative45975
Negative (%)100.0%
Memory size359.3 KiB
2025-02-19T00:20:03.097481image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-0.063232
5-th percentile-0.000917
Q1-0.000461
median-0.000352
Q3-0.000271
95-th percentile-0.0001947
Maximum-0.000118
Range0.063114
Interquartile range (IQR)0.00019

Descriptive statistics

Standard deviation0.0009768478684
Coefficient of variation (CV)-2.008938617
Kurtosis968.6714413
Mean-0.0004862507297
Median Absolute Deviation (MAD)9 × 10-5
Skewness-22.74225641
Sum-22.3553773
Variance9.542317579 × 10-7
MonotonicityNot monotonic
2025-02-19T00:20:03.275628image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.000352 9024
 
19.6%
-0.000273 292
 
0.6%
-0.000236 260
 
0.6%
-0.000254 232
 
0.5%
-0.000249 209
 
0.5%
-0.000253 208
 
0.5%
-0.000208 199
 
0.4%
-0.000201 191
 
0.4%
-0.000268 191
 
0.4%
-0.000217 186
 
0.4%
Other values (1092) 34983
76.1%
ValueCountFrequency (%)
-0.063232 2
 
< 0.1%
-0.039434 2
 
< 0.1%
-0.020612 4
< 0.1%
-0.017417 8
< 0.1%
-0.017262 7
< 0.1%
ValueCountFrequency (%)
-0.000118 2
 
< 0.1%
-0.000122 5
< 0.1%
-0.000127 2
 
< 0.1%
-0.000129 7
< 0.1%
-0.000135 4
< 0.1%
Distinct468
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.9 MiB
2025-02-19T00:20:03.473851image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.480130506
Min length7

Characters and Unicode

Total characters435849
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)0.1%

Sample

1st rowunknown
2nd rowunknown
3rd row2014-07-23
4th row2014-05-14
5th row2023-09-19
ValueCountFrequency (%)
unknown 7967
17.3%
2018-09-25 2840
 
6.2%
2014-11-21 2721
 
5.9%
2017-05-08 2715
 
5.9%
2015-08-25 2700
 
5.9%
2014-11-18 2679
 
5.8%
2013-10-28 2306
 
5.0%
2018-09-04 2225
 
4.8%
2016-05-06 2202
 
4.8%
2019-04-16 1953
 
4.2%
Other values (458) 15667
34.1%
2025-02-19T00:20:03.719513image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 81144
18.6%
- 76016
17.4%
2 67983
15.6%
1 62869
14.4%
n 23901
 
5.5%
8 19412
 
4.5%
5 19151
 
4.4%
4 18180
 
4.2%
6 12565
 
2.9%
9 10361
 
2.4%
Other values (6) 44267
10.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 435849
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 81144
18.6%
- 76016
17.4%
2 67983
15.6%
1 62869
14.4%
n 23901
 
5.5%
8 19412
 
4.5%
5 19151
 
4.4%
4 18180
 
4.2%
6 12565
 
2.9%
9 10361
 
2.4%
Other values (6) 44267
10.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 435849
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 81144
18.6%
- 76016
17.4%
2 67983
15.6%
1 62869
14.4%
n 23901
 
5.5%
8 19412
 
4.5%
5 19151
 
4.4%
4 18180
 
4.2%
6 12565
 
2.9%
9 10361
 
2.4%
Other values (6) 44267
10.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 435849
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 81144
18.6%
- 76016
17.4%
2 67983
15.6%
1 62869
14.4%
n 23901
 
5.5%
8 19412
 
4.5%
5 19151
 
4.4%
4 18180
 
4.2%
6 12565
 
2.9%
9 10361
 
2.4%
Other values (6) 44267
10.2%
Distinct292
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.9 MiB
2025-02-19T00:20:03.958041image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length16
Median length7
Mean length8.388841762
Min length7

Characters and Unicode

Total characters385677
Distinct characters18
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)0.1%

Sample

1st rowunknown
2nd rowunknown
3rd row2011-08
4th row2008-01
5th row2023-08
ValueCountFrequency (%)
unknown 7966
16.4%
2018-08-16 2732
 
5.6%
2014-12-18 2721
 
5.6%
00:00 2715
 
5.6%
2017-08-31 2715
 
5.6%
2015-09-24 2701
 
5.5%
2014-12-04 2679
 
5.5%
2014-01-08 2306
 
4.7%
2016-05 2279
 
4.7%
2018-10 2133
 
4.4%
Other values (283) 17743
36.4%
2025-02-19T00:20:04.250828image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 84963
22.0%
1 56431
14.6%
2 55828
14.5%
- 53863
14.0%
n 23898
 
6.2%
8 18254
 
4.7%
4 16121
 
4.2%
7 8671
 
2.2%
6 8597
 
2.2%
3 8563
 
2.2%
Other values (8) 50488
13.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 385677
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 84963
22.0%
1 56431
14.6%
2 55828
14.5%
- 53863
14.0%
n 23898
 
6.2%
8 18254
 
4.7%
4 16121
 
4.2%
7 8671
 
2.2%
6 8597
 
2.2%
3 8563
 
2.2%
Other values (8) 50488
13.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 385677
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 84963
22.0%
1 56431
14.6%
2 55828
14.5%
- 53863
14.0%
n 23898
 
6.2%
8 18254
 
4.7%
4 16121
 
4.2%
7 8671
 
2.2%
6 8597
 
2.2%
3 8563
 
2.2%
Other values (8) 50488
13.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 385677
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 84963
22.0%
1 56431
14.6%
2 55828
14.5%
- 53863
14.0%
n 23898
 
6.2%
8 18254
 
4.7%
4 16121
 
4.2%
7 8671
 
2.2%
6 8597
 
2.2%
3 8563
 
2.2%
Other values (8) 50488
13.1%
Distinct439
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.9 MiB
2025-02-19T00:20:04.441321image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length19
Median length10
Mean length9.483132137
Min length7

Characters and Unicode

Total characters435987
Distinct characters18
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)0.1%

Sample

1st rowunknown
2nd rowunknown
3rd row2014-07-23
4th row2014-05-14
5th row2023-09-19
ValueCountFrequency (%)
unknown 7966
17.3%
2018-09-25 2732
 
5.9%
2014-11-21 2721
 
5.9%
2017-05-08 2715
 
5.9%
2015-08-25 2700
 
5.9%
2014-11-18 2679
 
5.8%
2018-09-06 2321
 
5.0%
2013-10-28 2306
 
5.0%
2016-05-10 2260
 
4.9%
2019-04-18 1969
 
4.3%
Other values (432) 15621
34.0%
2025-02-19T00:20:04.632646image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 80556
18.5%
- 76018
17.4%
2 67151
15.4%
1 66458
15.2%
n 23898
 
5.5%
8 22368
 
5.1%
5 19564
 
4.5%
4 15930
 
3.7%
9 10139
 
2.3%
6 9354
 
2.1%
Other values (8) 44551
10.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 435987
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 80556
18.5%
- 76018
17.4%
2 67151
15.4%
1 66458
15.2%
n 23898
 
5.5%
8 22368
 
5.1%
5 19564
 
4.5%
4 15930
 
3.7%
9 10139
 
2.3%
6 9354
 
2.1%
Other values (8) 44551
10.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 435987
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 80556
18.5%
- 76018
17.4%
2 67151
15.4%
1 66458
15.2%
n 23898
 
5.5%
8 22368
 
5.1%
5 19564
 
4.5%
4 15930
 
3.7%
9 10139
 
2.3%
6 9354
 
2.1%
Other values (8) 44551
10.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 435987
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 80556
18.5%
- 76018
17.4%
2 67151
15.4%
1 66458
15.2%
n 23898
 
5.5%
8 22368
 
5.1%
5 19564
 
4.5%
4 15930
 
3.7%
9 10139
 
2.3%
6 9354
 
2.1%
Other values (8) 44551
10.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.9 MiB
2025-02-19T00:20:04.690611image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length9
Median length9
Mean length8.40228385
Min length7

Characters and Unicode

Total characters386295
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowConfirmed
2nd rowConfirmed
3rd rowunknown
4th rowunknown
5th rowunknown
ValueCountFrequency (%)
confirmed 32235
70.1%
unknown 13740
29.9%
2025-02-19T00:20:04.810498image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 73455
19.0%
o 45975
11.9%
C 32235
8.3%
f 32235
8.3%
i 32235
8.3%
r 32235
8.3%
m 32235
8.3%
e 32235
8.3%
d 32235
8.3%
u 13740
 
3.6%
Other values (2) 27480
 
7.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 386295
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 73455
19.0%
o 45975
11.9%
C 32235
8.3%
f 32235
8.3%
i 32235
8.3%
r 32235
8.3%
m 32235
8.3%
e 32235
8.3%
d 32235
8.3%
u 13740
 
3.6%
Other values (2) 27480
 
7.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 386295
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 73455
19.0%
o 45975
11.9%
C 32235
8.3%
f 32235
8.3%
i 32235
8.3%
r 32235
8.3%
m 32235
8.3%
e 32235
8.3%
d 32235
8.3%
u 13740
 
3.6%
Other values (2) 27480
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 386295
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 73455
19.0%
o 45975
11.9%
C 32235
8.3%
f 32235
8.3%
i 32235
8.3%
r 32235
8.3%
m 32235
8.3%
e 32235
8.3%
d 32235
8.3%
u 13740
 
3.6%
Other values (2) 27480
 
7.1%

mass
Real number (ℝ)

Distinct2153
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.748521445
Minimum6.3 × 10-5
Maximum74.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:20:04.857151image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum6.3 × 10-5
5-th percentile0.0261
Q11.8
median1.8
Q31.8
95-th percentile4
Maximum74.6
Range74.599937
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6.736171728
Coefficient of variation (CV)2.450834699
Kurtosis47.90954869
Mean2.748521445
Median Absolute Deviation (MAD)0
Skewness6.712818561
Sum126363.2734
Variance45.37600954
MonotonicityNot monotonic
2025-02-19T00:20:04.949652image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.8 35323
76.8%
60 108
 
0.2%
0.019 71
 
0.2%
0.009 70
 
0.2%
0.013 60
 
0.1%
50 59
 
0.1%
30 57
 
0.1%
0.11 52
 
0.1%
0.011 52
 
0.1%
0.023 51
 
0.1%
Other values (2143) 10072
 
21.9%
ValueCountFrequency (%)
6.3 × 10-58
< 0.1%
7 × 10-51
 
< 0.1%
0.00019 3
 
< 0.1%
0.00021 15
< 0.1%
0.00076 1
 
< 0.1%
ValueCountFrequency (%)
74.6 1
< 0.1%
73.4 1
< 0.1%
72.07 1
< 0.1%
72 2
< 0.1%
71.7 1
< 0.1%

mass_error_min
Real number (ℝ)

Distinct978
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite119
Infinite (%)0.3%
Meaninf
Minimum0
Maximuminf
Zeros41
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:20:05.026232image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.006028
Q10.11
median0.11
Q30.11
95-th percentile0.24
Maximuminf
Rangeinf
Interquartile range (IQR)0

Descriptive statistics

Standard deviationnan
Coefficient of variation (CV)nan
Kurtosisnan
Meaninf
Median Absolute Deviation (MAD)0
Skewnessnan
Suminf
Variancenan
MonotonicityNot monotonic
2025-02-19T00:20:05.093771image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.11 36588
79.6%
0.08 195
 
0.4%
0.006 163
 
0.4%
0.003 159
 
0.3%
0.03 125
 
0.3%
0.1 123
 
0.3%
inf 119
 
0.3%
0.01 115
 
0.3%
0.04 113
 
0.2%
0.13 113
 
0.2%
Other values (968) 8162
 
17.8%
ValueCountFrequency (%)
0 41
0.1%
4 × 10-66
 
< 0.1%
0.00012 15
 
< 0.1%
0.000154 5
 
< 0.1%
0.00016 1
 
< 0.1%
ValueCountFrequency (%)
inf 119
0.3%
210 1
 
< 0.1%
56.1 1
 
< 0.1%
54.9 1
 
< 0.1%
53.5 1
 
< 0.1%

mass_error_max
Real number (ℝ)

Distinct978
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite119
Infinite (%)0.3%
Meaninf
Minimum0
Maximuminf
Zeros41
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:20:05.157494image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.006028
Q10.11
median0.11
Q30.11
95-th percentile0.24
Maximuminf
Rangeinf
Interquartile range (IQR)0

Descriptive statistics

Standard deviationnan
Coefficient of variation (CV)nan
Kurtosisnan
Meaninf
Median Absolute Deviation (MAD)0
Skewnessnan
Suminf
Variancenan
MonotonicityNot monotonic
2025-02-19T00:20:05.220952image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.11 36588
79.6%
0.08 195
 
0.4%
0.006 163
 
0.4%
0.003 159
 
0.3%
0.03 125
 
0.3%
0.1 123
 
0.3%
inf 119
 
0.3%
0.01 115
 
0.3%
0.04 113
 
0.2%
0.13 113
 
0.2%
Other values (968) 8162
 
17.8%
ValueCountFrequency (%)
0 41
0.1%
4 × 10-66
 
< 0.1%
0.00012 15
 
< 0.1%
0.000154 5
 
< 0.1%
0.00016 1
 
< 0.1%
ValueCountFrequency (%)
inf 119
0.3%
210 1
 
< 0.1%
56.1 1
 
< 0.1%
54.9 1
 
< 0.1%
53.5 1
 
< 0.1%

planet_radius_y
Real number (ℝ)

Distinct1787
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2977766678
Minimum2 × 10-6
Maximum18.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:20:05.284458image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum2 × 10-6
5-th percentile0.102
Q10.179
median0.221
Q30.233
95-th percentile1.08
Maximum18.8
Range18.799998
Interquartile range (IQR)0.054

Descriptive statistics

Standard deviation0.3598336169
Coefficient of variation (CV)1.208400979
Kurtosis342.3058292
Mean0.2977766678
Median Absolute Deviation (MAD)0.027
Skewness11.43769589
Sum13690.2823
Variance0.1294802318
MonotonicityNot monotonic
2025-02-19T00:20:05.348367image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.221 13823
30.1%
0.232 3383
 
7.4%
0.178 337
 
0.7%
0.136 274
 
0.6%
0.211 255
 
0.6%
0.128 232
 
0.5%
0.17 223
 
0.5%
0.194 214
 
0.5%
0.112 208
 
0.5%
0.145 195
 
0.4%
Other values (1777) 26831
58.4%
ValueCountFrequency (%)
2 × 10-61
 
< 0.1%
6.2 × 10-51
 
< 0.1%
0.02543 11
< 0.1%
0.026 13
< 0.1%
0.03595 1
 
< 0.1%
ValueCountFrequency (%)
18.8 1
< 0.1%
14.5 1
< 0.1%
13.8 1
< 0.1%
11.3 1
< 0.1%
11.2 1
< 0.1%

radius_error_min
Real number (ℝ)

Skewed 

Distinct417
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.03227967139
Minimum0
Maximum48
Zeros15
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:20:05.423589image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.006
Q10.017
median0.021
Q30.026
95-th percentile0.096
Maximum48
Range48
Interquartile range (IQR)0.009

Descriptive statistics

Standard deviation0.2319165089
Coefficient of variation (CV)7.184599437
Kurtosis39813.11189
Mean0.03227967139
Median Absolute Deviation (MAD)0.004
Skewness192.915668
Sum1484.057892
Variance0.05378526708
MonotonicityNot monotonic
2025-02-19T00:20:05.480680image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.021 19073
41.5%
0.012 1322
 
2.9%
0.009 936
 
2.0%
0.007 766
 
1.7%
0.008 758
 
1.6%
0.01 724
 
1.6%
0.015 679
 
1.5%
0.006 661
 
1.4%
0.02 658
 
1.4%
0.011 649
 
1.4%
Other values (407) 19749
43.0%
ValueCountFrequency (%)
0 15
< 0.1%
0.000259 1
 
< 0.1%
0.0003 12
< 0.1%
0.00031 14
< 0.1%
0.00045 4
 
< 0.1%
ValueCountFrequency (%)
48 1
 
< 0.1%
2.9 1
 
< 0.1%
2.378 11
< 0.1%
1.902 8
< 0.1%
1.9 2
 
< 0.1%

radius_error_max
Real number (ℝ)

Skewed 

Distinct417
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.03227967139
Minimum0
Maximum48
Zeros15
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:20:05.538317image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.006
Q10.017
median0.021
Q30.026
95-th percentile0.096
Maximum48
Range48
Interquartile range (IQR)0.009

Descriptive statistics

Standard deviation0.2319165089
Coefficient of variation (CV)7.184599437
Kurtosis39813.11189
Mean0.03227967139
Median Absolute Deviation (MAD)0.004
Skewness192.915668
Sum1484.057892
Variance0.05378526708
MonotonicityNot monotonic
2025-02-19T00:20:05.595568image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.021 19073
41.5%
0.012 1322
 
2.9%
0.009 936
 
2.0%
0.007 766
 
1.7%
0.008 758
 
1.6%
0.01 724
 
1.6%
0.015 679
 
1.5%
0.006 661
 
1.4%
0.02 658
 
1.4%
0.011 649
 
1.4%
Other values (407) 19749
43.0%
ValueCountFrequency (%)
0 15
< 0.1%
0.000259 1
 
< 0.1%
0.0003 12
< 0.1%
0.00031 14
< 0.1%
0.00045 4
 
< 0.1%
ValueCountFrequency (%)
48 1
 
< 0.1%
2.9 1
 
< 0.1%
2.378 11
< 0.1%
1.902 8
< 0.1%
1.9 2
 
< 0.1%

planet_period_y
Real number (ℝ)

Skewed 

Distinct6084
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1030.455074
Minimum0.001226788432
Maximum12811500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:20:05.807121image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.001226788432
5-th percentile2.05387982
Q17.07142
median11.456085
Q316.1457
95-th percentile127.282184
Maximum12811500
Range12811500
Interquartile range (IQR)9.07428

Descriptive statistics

Standard deviation85863.56911
Coefficient of variation (CV)83.32587346
Kurtosis16506.22742
Mean1030.455074
Median Absolute Deviation (MAD)4.4753889
Skewness125.1672019
Sum47375172.03
Variance7372552501
MonotonicityNot monotonic
2025-02-19T00:20:05.919228image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11.456085 15174
33.0%
0.837491 23
 
0.1%
3.52472 22
 
< 0.1%
2.64394 22
 
< 0.1%
45.2946 20
 
< 0.1%
1.580404497 20
 
< 0.1%
39.7922 19
 
< 0.1%
4.8854892 19
 
< 0.1%
3.2346996 18
 
< 0.1%
4.4379629 18
 
< 0.1%
Other values (6074) 30620
66.6%
ValueCountFrequency (%)
0.001226788432 1
< 0.1%
0.0078 1
< 0.1%
0.011806 1
< 0.1%
0.012083333 1
< 0.1%
0.0125 1
< 0.1%
ValueCountFrequency (%)
12811500 1
< 0.1%
10034580 1
< 0.1%
8035500 1
< 0.1%
1800000 1
< 0.1%
1178220 1
< 0.1%

orbital_period_error_min
Real number (ℝ)

Skewed 

Distinct2542
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3110448.58
Minimum0
Maximum1.43000178 × 1011
Zeros14
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:20:05.982497image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.42 × 10-6
Q13.122 × 10-5
median7.788 × 10-5
Q30.000107
95-th percentile0.0028
Maximum1.43000178 × 1011
Range1.43000178 × 1011
Interquartile range (IQR)7.578 × 10-5

Descriptive statistics

Standard deviation666923021.3
Coefficient of variation (CV)214.4137748
Kurtosis45975
Mean3110448.58
Median Absolute Deviation (MAD)3.788 × 10-5
Skewness214.4178164
Sum1.430028735 × 1011
Variance4.447863163 × 1017
MonotonicityNot monotonic
2025-02-19T00:20:06.077110image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.788 × 10-513749
29.9%
0.000107 3662
 
8.0%
1 × 10-5289
 
0.6%
2 × 10-5274
 
0.6%
8 × 10-6206
 
0.4%
9 × 10-6200
 
0.4%
3 × 10-6199
 
0.4%
6 × 10-6192
 
0.4%
1.1 × 10-5191
 
0.4%
5 × 10-6190
 
0.4%
Other values (2532) 26823
58.3%
ValueCountFrequency (%)
0 14
< 0.1%
2 × 10-112
 
< 0.1%
4 × 10-111
 
< 0.1%
1 × 10-102
 
< 0.1%
1.3 × 10-101
 
< 0.1%
ValueCountFrequency (%)
1.43000178 × 10111
< 0.1%
825000 1
< 0.1%
475000 1
< 0.1%
365000 1
< 0.1%
100000 1
< 0.1%

orbital_period_error_max
Real number (ℝ)

Skewed 

Distinct2542
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3110448.58
Minimum0
Maximum1.43000178 × 1011
Zeros14
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:20:06.141269image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.42 × 10-6
Q13.122 × 10-5
median7.788 × 10-5
Q30.000107
95-th percentile0.0028
Maximum1.43000178 × 1011
Range1.43000178 × 1011
Interquartile range (IQR)7.578 × 10-5

Descriptive statistics

Standard deviation666923021.3
Coefficient of variation (CV)214.4137748
Kurtosis45975
Mean3110448.58
Median Absolute Deviation (MAD)3.788 × 10-5
Skewness214.4178164
Sum1.430028735 × 1011
Variance4.447863163 × 1017
MonotonicityNot monotonic
2025-02-19T00:20:06.220450image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.788 × 10-513749
29.9%
0.000107 3662
 
8.0%
1 × 10-5289
 
0.6%
2 × 10-5274
 
0.6%
8 × 10-6206
 
0.4%
9 × 10-6200
 
0.4%
3 × 10-6199
 
0.4%
6 × 10-6192
 
0.4%
1.1 × 10-5191
 
0.4%
5 × 10-6190
 
0.4%
Other values (2532) 26823
58.3%
ValueCountFrequency (%)
0 14
< 0.1%
2 × 10-112
 
< 0.1%
4 × 10-111
 
< 0.1%
1 × 10-102
 
< 0.1%
1.3 × 10-101
 
< 0.1%
ValueCountFrequency (%)
1.43000178 × 10111
< 0.1%
825000 1
< 0.1%
475000 1
< 0.1%
365000 1
< 0.1%
100000 1
< 0.1%

semi_major_axis_y
Real number (ℝ)

Skewed 

Distinct2887
Distinct (%)6.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.12308242
Minimum0.0002468
Maximum38000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:20:06.283712image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.0002468
5-th percentile0.03977
Q10.12
median0.12
Q30.12
95-th percentile0.554
Maximum38000
Range37999.99975
Interquartile range (IQR)0

Descriptive statistics

Standard deviation412.4877409
Coefficient of variation (CV)29.20663696
Kurtosis3495.605157
Mean14.12308242
Median Absolute Deviation (MAD)0
Skewness52.98021406
Sum649308.714
Variance170146.1364
MonotonicityNot monotonic
2025-02-19T00:20:06.353976image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.12 27595
60.0%
0.08 130
 
0.3%
0.11 125
 
0.3%
0.09 117
 
0.3%
0.087 116
 
0.3%
0.117 109
 
0.2%
0.05 108
 
0.2%
0.066 105
 
0.2%
0.075 104
 
0.2%
0.061 104
 
0.2%
Other values (2877) 17362
37.8%
ValueCountFrequency (%)
0.0002468 1
< 0.1%
0.000834 1
< 0.1%
0.00087 1
< 0.1%
0.001147 1
< 0.1%
0.00116 1
< 0.1%
ValueCountFrequency (%)
38000 1
< 0.1%
28000 1
< 0.1%
27000 1
< 0.1%
25000 1
< 0.1%
24000 1
< 0.1%
Distinct1060
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size2.9 MiB
2025-02-19T00:20:06.473886image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.103425775
Min length7

Characters and Unicode

Total characters418530
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique268 ?
Unique (%)0.6%

Sample

1st row2024-06-14
2nd row2024-08-01
3rd rowunknown
4th rowunknown
5th rowunknown
ValueCountFrequency (%)
2021-02-05 23789
51.7%
unknown 13740
29.9%
2024-05-28 178
 
0.4%
2024-08-01 149
 
0.3%
2024-07-28 122
 
0.3%
2024-07-29 104
 
0.2%
2024-06-28 91
 
0.2%
2024-06-30 86
 
0.2%
2024-08-02 81
 
0.2%
2024-07-31 81
 
0.2%
Other values (1050) 7554
 
16.4%
2025-02-19T00:20:06.663792image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 91903
22.0%
0 90715
21.7%
- 64470
15.4%
n 41220
9.8%
1 32378
 
7.7%
5 25661
 
6.1%
u 13740
 
3.3%
k 13740
 
3.3%
o 13740
 
3.3%
w 13740
 
3.3%
Other values (6) 17223
 
4.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 418530
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 91903
22.0%
0 90715
21.7%
- 64470
15.4%
n 41220
9.8%
1 32378
 
7.7%
5 25661
 
6.1%
u 13740
 
3.3%
k 13740
 
3.3%
o 13740
 
3.3%
w 13740
 
3.3%
Other values (6) 17223
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 418530
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 91903
22.0%
0 90715
21.7%
- 64470
15.4%
n 41220
9.8%
1 32378
 
7.7%
5 25661
 
6.1%
u 13740
 
3.3%
k 13740
 
3.3%
o 13740
 
3.3%
w 13740
 
3.3%
Other values (6) 17223
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 418530
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 91903
22.0%
0 90715
21.7%
- 64470
15.4%
n 41220
9.8%
1 32378
 
7.7%
5 25661
 
6.1%
u 13740
 
3.3%
k 13740
 
3.3%
o 13740
 
3.3%
w 13740
 
3.3%
Other values (6) 17223
 
4.1%
Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.4 MiB
2025-02-19T00:20:06.748821image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length38
Median length35
Mean length19.43014682
Min length7

Characters and Unicode

Total characters893301
Distinct characters24
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPublished in a refereed paper
2nd rowPublished in a refereed paper
3rd rowunknown
4th rowunknown
5th rowunknown
ValueCountFrequency (%)
a 32235
20.8%
announced 20280
13.1%
on 20280
13.1%
website 20112
13.0%
unknown 13740
8.9%
published 11692
 
7.6%
in 11692
 
7.6%
refereed 11692
 
7.6%
paper 11692
 
7.6%
professional 431
 
0.3%
Other values (4) 957
 
0.6%
2025-02-19T00:20:06.842085image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 135062
15.1%
e 131854
14.8%
108828
12.2%
o 55856
 
6.3%
u 46238
 
5.2%
a 44621
 
5.0%
i 44190
 
4.9%
d 43927
 
4.9%
r 35938
 
4.0%
w 33852
 
3.8%
Other values (14) 212935
23.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 893301
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 135062
15.1%
e 131854
14.8%
108828
12.2%
o 55856
 
6.3%
u 46238
 
5.2%
a 44621
 
5.0%
i 44190
 
4.9%
d 43927
 
4.9%
r 35938
 
4.0%
w 33852
 
3.8%
Other values (14) 212935
23.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 893301
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 135062
15.1%
e 131854
14.8%
108828
12.2%
o 55856
 
6.3%
u 46238
 
5.2%
a 44621
 
5.0%
i 44190
 
4.9%
d 43927
 
4.9%
r 35938
 
4.0%
w 33852
 
3.8%
Other values (14) 212935
23.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 893301
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 135062
15.1%
e 131854
14.8%
108828
12.2%
o 55856
 
6.3%
u 46238
 
5.2%
a 44621
 
5.0%
i 44190
 
4.9%
d 43927
 
4.9%
r 35938
 
4.0%
w 33852
 
3.8%
Other values (14) 212935
23.8%
Distinct33
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size3.0 MiB
2025-02-19T00:20:06.888259image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length36
Median length15
Mean length12.38616639
Min length3

Characters and Unicode

Total characters569454
Distinct characters29
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)< 0.1%

Sample

1st rowRadial Velocity, Astrometry
2nd rowRadial Velocity
3rd rowunknown
4th rowunknown
5th rowunknown
ValueCountFrequency (%)
primary 28374
37.0%
transit 28374
37.0%
unknown 13740
17.9%
radial 1984
 
2.6%
velocity 1984
 
2.6%
imaging 1058
 
1.4%
microlensing 454
 
0.6%
astrometry 218
 
0.3%
timing 182
 
0.2%
ttv 141
 
0.2%
Other values (2) 133
 
0.2%
2025-02-19T00:20:06.997184image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 86127
15.1%
n 71760
12.6%
i 63082
11.1%
a 61792
10.9%
t 30927
 
5.4%
30667
 
5.4%
y 30576
 
5.4%
m 29850
 
5.2%
s 29046
 
5.1%
T 28838
 
5.1%
Other values (19) 106789
18.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 569454
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r 86127
15.1%
n 71760
12.6%
i 63082
11.1%
a 61792
10.9%
t 30927
 
5.4%
30667
 
5.4%
y 30576
 
5.4%
m 29850
 
5.2%
s 29046
 
5.1%
T 28838
 
5.1%
Other values (19) 106789
18.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 569454
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r 86127
15.1%
n 71760
12.6%
i 63082
11.1%
a 61792
10.9%
t 30927
 
5.4%
30667
 
5.4%
y 30576
 
5.4%
m 29850
 
5.2%
s 29046
 
5.1%
T 28838
 
5.1%
Other values (19) 106789
18.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 569454
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r 86127
15.1%
n 71760
12.6%
i 63082
11.1%
a 61792
10.9%
t 30927
 
5.4%
30667
 
5.4%
y 30576
 
5.4%
m 29850
 
5.2%
s 29046
 
5.1%
T 28838
 
5.1%
Other values (19) 106789
18.8%
Distinct4849
Distinct (%)10.5%
Missing0
Missing (%)0.0%
Memory size5.1 MiB
2025-02-19T00:20:07.109226image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length206
Median length192
Mean length58.91056009
Min length5

Characters and Unicode

Total characters2708413
Distinct characters77
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2216 ?
Unique (%)4.8%

Sample

1st rowHD 10697 b
2nd rowunkown
3rd rowunknown
4th rowunknown
5th rowunknown
ValueCountFrequency (%)
b 68412
19.8%
2mass 25054
 
7.3%
wise 23395
 
6.8%
kic 23382
 
6.8%
c 20472
 
5.9%
unknown 13740
 
4.0%
d 7279
 
2.1%
unkown 4809
 
1.4%
epic 2827
 
0.8%
e 2528
 
0.7%
Other values (15498) 153077
44.4%
2025-02-19T00:20:07.315928image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
308919
 
11.4%
1 222167
 
8.2%
0 197102
 
7.3%
2 173548
 
6.4%
4 153447
 
5.7%
3 124791
 
4.6%
, 121925
 
4.5%
9 117943
 
4.4%
5 117654
 
4.3%
I 98334
 
3.6%
Other values (67) 1072583
39.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2708413
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
308919
 
11.4%
1 222167
 
8.2%
0 197102
 
7.3%
2 173548
 
6.4%
4 153447
 
5.7%
3 124791
 
4.6%
, 121925
 
4.5%
9 117943
 
4.4%
5 117654
 
4.3%
I 98334
 
3.6%
Other values (67) 1072583
39.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2708413
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
308919
 
11.4%
1 222167
 
8.2%
0 197102
 
7.3%
2 173548
 
6.4%
4 153447
 
5.7%
3 124791
 
4.6%
, 121925
 
4.5%
9 117943
 
4.4%
5 117654
 
4.3%
I 98334
 
3.6%
Other values (67) 1072583
39.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2708413
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
308919
 
11.4%
1 222167
 
8.2%
0 197102
 
7.3%
2 173548
 
6.4%
4 153447
 
5.7%
3 124791
 
4.6%
, 121925
 
4.5%
9 117943
 
4.4%
5 117654
 
4.3%
I 98334
 
3.6%
Other values (67) 1072583
39.6%

ra_y
Real number (ℝ)

Distinct5707
Distinct (%)12.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean271.0835065
Minimum0
Maximum359.975
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:20:07.386838image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile111.8972792
Q1286.344287
median289.651263
Q3292.19971
95-th percentile298.652714
Maximum359.975
Range359.975
Interquartile range (IQR)5.855423

Descriptive statistics

Standard deviation59.81864581
Coefficient of variation (CV)0.2206650142
Kurtosis7.541704149
Mean271.0835065
Median Absolute Deviation (MAD)2.879287
Skewness-2.857707127
Sum12463064.21
Variance3578.270386
MonotonicityNot monotonic
2025-02-19T00:20:07.442979image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
289.651263 13761
29.9%
297.115123 97
 
0.2%
296.112564 83
 
0.2%
297.842398 76
 
0.2%
298.652714 75
 
0.2%
281.482749 73
 
0.2%
289.077548 67
 
0.1%
283.212747 63
 
0.1%
284.940997 62
 
0.1%
291.111883 60
 
0.1%
Other values (5697) 31558
68.6%
ValueCountFrequency (%)
0 2
< 0.1%
0.056437 1
< 0.1%
0.06558333333 1
< 0.1%
0.187500015 1
< 0.1%
0.3006871114 1
< 0.1%
ValueCountFrequency (%)
359.975 2
< 0.1%
359.918122 1
 
< 0.1%
359.9 2
< 0.1%
359.7916667 3
< 0.1%
359.7166667 3
< 0.1%

dec_y
Real number (ℝ)

Distinct5729
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.65614528
Minimum-88.12111112
Maximum86.86033333
Zeros2
Zeros (%)< 0.1%
Negative4436
Negative (%)9.6%
Memory size359.3 KiB
2025-02-19T00:20:07.490481image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-88.12111112
5-th percentile-24.4289
Q140.61614
median42.811783
Q344.968224
95-th percentile49.781158
Maximum86.86033333
Range174.9814445
Interquartile range (IQR)4.352084

Descriptive statistics

Standard deviation23.13488291
Coefficient of variation (CV)0.6488329777
Kurtosis6.740336337
Mean35.65614528
Median Absolute Deviation (MAD)2.173968
Skewness-2.635198104
Sum1639291.279
Variance535.2228074
MonotonicityNot monotonic
2025-02-19T00:20:07.676134image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42.811783 13763
29.9%
41.909138 97
 
0.2%
39.978779 83
 
0.2%
46.574281 76
 
0.2%
43.955017 75
 
0.2%
47.208031 73
 
0.2%
46.005222 67
 
0.1%
45.349865 63
 
0.1%
46.56654 62
 
0.1%
39.949104 60
 
0.1%
Other values (5719) 31556
68.6%
ValueCountFrequency (%)
-88.12111112 1
 
< 0.1%
-86.98000003 2
< 0.1%
-84.2313889 1
 
< 0.1%
-83.74388891 2
< 0.1%
-83.12972224 4
< 0.1%
ValueCountFrequency (%)
86.86033333 3
< 0.1%
85.73611113 2
 
< 0.1%
85.23333334 6
< 0.1%
85.1295 3
< 0.1%
84.59956166 1
 
< 0.1%

mag_j
Real number (ℝ)

Distinct2158
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.79628866
Minimum2.57
Maximum19.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:20:07.737696image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum2.57
5-th percentile10.846
Q112.782
median12.782
Q313.285
95-th percentile14.252
Maximum19.6
Range17.03
Interquartile range (IQR)0.503

Descriptive statistics

Standard deviation1.072853191
Coefficient of variation (CV)0.08384096513
Kurtosis12.01149853
Mean12.79628866
Median Absolute Deviation (MAD)0.19
Skewness-2.329844934
Sum588309.3711
Variance1.15101397
MonotonicityNot monotonic
2025-02-19T00:20:07.792945image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12.782 19800
43.1%
12.548 108
 
0.2%
13.875 105
 
0.2%
13.28 95
 
0.2%
12.871 94
 
0.2%
12.631 93
 
0.2%
13.408 87
 
0.2%
12.729 85
 
0.2%
14.095 85
 
0.2%
12.954 83
 
0.2%
Other values (2148) 25340
55.1%
ValueCountFrequency (%)
2.57 1
< 0.1%
2.58 1
< 0.1%
2.82 2
< 0.1%
2.85 1
< 0.1%
2.89 1
< 0.1%
ValueCountFrequency (%)
19.6 1
< 0.1%
19 1
< 0.1%
17.85 1
< 0.1%
17.212 1
< 0.1%
16.77 1
< 0.1%

mag_h
Real number (ℝ)

Distinct2166
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.40584145
Minimum1.81
Maximum23.38
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:20:07.843663image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1.81
5-th percentile10.506
Q112.386
median12.386
Q312.869
95-th percentile13.87
Maximum23.38
Range21.57
Interquartile range (IQR)0.483

Descriptive statistics

Standard deviation1.062756164
Coefficient of variation (CV)0.08566578643
Kurtosis12.75190461
Mean12.40584145
Median Absolute Deviation (MAD)0.183
Skewness-2.351357485
Sum570358.5607
Variance1.129450665
MonotonicityNot monotonic
2025-02-19T00:20:07.905745image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12.386 19880
43.2%
12.237 116
 
0.3%
13.527 97
 
0.2%
12.354 93
 
0.2%
12.283 86
 
0.2%
12.065 82
 
0.2%
13.718 82
 
0.2%
13.341 80
 
0.2%
12.901 77
 
0.2%
11.824 75
 
0.2%
Other values (2156) 25307
55.0%
ValueCountFrequency (%)
1.81 1
< 0.1%
2.04 1
< 0.1%
2.11 1
< 0.1%
2.32 2
< 0.1%
2.35 1
< 0.1%
ValueCountFrequency (%)
23.38 1
< 0.1%
18.08 1
< 0.1%
17.21 1
< 0.1%
17.17 2
< 0.1%
16.29 1
< 0.1%

star_distance
Real number (ℝ)

Distinct4022
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean686.1195808
Minimum1.295
Maximum12000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:20:07.969642image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1.295
5-th percentile50
Q1423
median621.24
Q3799.75
95-th percentile1379.9
Maximum12000
Range11998.705
Interquartile range (IQR)376.75

Descriptive statistics

Standard deviation631.1637457
Coefficient of variation (CV)0.9199034153
Kurtosis61.79541716
Mean686.1195808
Median Absolute Deviation (MAD)188.18
Skewness6.370378417
Sum31544347.73
Variance398367.6739
MonotonicityNot monotonic
2025-02-19T00:20:08.049211image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
621.24 13779
30.0%
317.83 632
 
1.4%
357 101
 
0.2%
658.59 97
 
0.2%
793 87
 
0.2%
326.85 76
 
0.2%
172 75
 
0.2%
108.13 73
 
0.2%
470 69
 
0.2%
1252.84 67
 
0.1%
Other values (4012) 30919
67.3%
ValueCountFrequency (%)
1.295 2
< 0.1%
1.82823 1
< 0.1%
1.998 2
< 0.1%
2.31 1
< 0.1%
2.42 1
< 0.1%
ValueCountFrequency (%)
12000 1
< 0.1%
11000 1
< 0.1%
10400 1
< 0.1%
10300 2
< 0.1%
9600 1
< 0.1%

star_distance_error_min
Real number (ℝ)

Distinct1809
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.75571648
Minimum-1900
Maximum4000
Zeros14
Zeros (%)< 0.1%
Negative11
Negative (%)< 0.1%
Memory size359.3 KiB
2025-02-19T00:20:08.115294image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-1900
5-th percentile0.54
Q13.73
median3.73
Q35.43
95-th percentile46.4
Maximum4000
Range5900
Interquartile range (IQR)1.7

Descriptive statistics

Standard deviation125.5280739
Coefficient of variation (CV)6.354012723
Kurtosis235.2262552
Mean19.75571648
Median Absolute Deviation (MAD)0
Skewness13.98713507
Sum908269.0651
Variance15757.29732
MonotonicityNot monotonic
2025-02-19T00:20:08.175494image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.73 26944
58.6%
1 184
 
0.4%
0.4 145
 
0.3%
3 128
 
0.3%
10 122
 
0.3%
0.22 111
 
0.2%
20 105
 
0.2%
30 104
 
0.2%
0.2 98
 
0.2%
6.57 97
 
0.2%
Other values (1799) 17937
39.0%
ValueCountFrequency (%)
-1900 1
 
< 0.1%
-20.9 1
 
< 0.1%
-3.038 4
< 0.1%
-2.784 2
< 0.1%
-1.9427 2
< 0.1%
ValueCountFrequency (%)
4000 1
< 0.1%
3640 1
< 0.1%
3520 1
< 0.1%
3200 1
< 0.1%
2950 1
< 0.1%

star_distance_error_max
Real number (ℝ)

Distinct1809
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.75571648
Minimum-1900
Maximum4000
Zeros14
Zeros (%)< 0.1%
Negative11
Negative (%)< 0.1%
Memory size359.3 KiB
2025-02-19T00:20:08.238207image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-1900
5-th percentile0.54
Q13.73
median3.73
Q35.43
95-th percentile46.4
Maximum4000
Range5900
Interquartile range (IQR)1.7

Descriptive statistics

Standard deviation125.5280739
Coefficient of variation (CV)6.354012723
Kurtosis235.2262552
Mean19.75571648
Median Absolute Deviation (MAD)0
Skewness13.98713507
Sum908269.0651
Variance15757.29732
MonotonicityNot monotonic
2025-02-19T00:20:08.311259image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.73 26944
58.6%
1 184
 
0.4%
0.4 145
 
0.3%
3 128
 
0.3%
10 122
 
0.3%
0.22 111
 
0.2%
20 105
 
0.2%
30 104
 
0.2%
0.2 98
 
0.2%
6.57 97
 
0.2%
Other values (1799) 17937
39.0%
ValueCountFrequency (%)
-1900 1
 
< 0.1%
-20.9 1
 
< 0.1%
-3.038 4
< 0.1%
-2.784 2
< 0.1%
-1.9427 2
< 0.1%
ValueCountFrequency (%)
4000 1
< 0.1%
3640 1
< 0.1%
3520 1
< 0.1%
3200 1
< 0.1%
2950 1
< 0.1%

star_metallicity_x
Real number (ℝ)

Zeros 

Distinct616
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.005667408809
Minimum-3.026
Maximum15.47
Zeros1063
Zeros (%)2.3%
Negative13791
Negative (%)30.0%
Memory size359.3 KiB
2025-02-19T00:20:08.365793image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-3.026
5-th percentile-0.29
Q1-0.03
median0.01
Q30.03
95-th percentile0.23
Maximum15.47
Range18.496
Interquartile range (IQR)0.06

Descriptive statistics

Standard deviation0.1682108618
Coefficient of variation (CV)-29.6803826
Kurtosis1564.057722
Mean-0.005667408809
Median Absolute Deviation (MAD)0.03
Skewness16.06324869
Sum-260.55912
Variance0.02829489403
MonotonicityNot monotonic
2025-02-19T00:20:08.433305image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.01 18047
39.3%
0 1063
 
2.3%
0.04 1058
 
2.3%
0.03 1018
 
2.2%
0.02 945
 
2.1%
0.05 862
 
1.9%
-0.01 792
 
1.7%
-0.03 755
 
1.6%
-0.02 625
 
1.4%
0.07 602
 
1.3%
Other values (606) 20208
44.0%
ValueCountFrequency (%)
-3.026 1
< 0.1%
-1.98 1
< 0.1%
-1.387 1
< 0.1%
-1.3 1
< 0.1%
-1.19 1
< 0.1%
ValueCountFrequency (%)
15.47 1
 
< 0.1%
0.89 5
< 0.1%
0.61 1
 
< 0.1%
0.6 1
 
< 0.1%
0.56 1
 
< 0.1%

star_metallicity_error_min
Real number (ℝ)

Skewed 

Distinct346
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2099890275
Minimum0
Maximum4500
Zeros7
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:20:08.524311image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.05
Q10.1
median0.1
Q30.106
95-th percentile0.186
Maximum4500
Range4500
Interquartile range (IQR)0.006

Descriptive statistics

Standard deviation20.9866269
Coefficient of variation (CV)99.9415405
Kurtosis45974.23059
Mean0.2099890275
Median Absolute Deviation (MAD)0
Skewness214.4151264
Sum9654.24554
Variance440.4385086
MonotonicityNot monotonic
2025-02-19T00:20:08.587946image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1 26478
57.6%
0.08 885
 
1.9%
0.04 779
 
1.7%
0.05 762
 
1.7%
0.07 608
 
1.3%
0.06 586
 
1.3%
0.16 450
 
1.0%
0.12 402
 
0.9%
0.03 386
 
0.8%
0.15 359
 
0.8%
Other values (336) 14280
31.1%
ValueCountFrequency (%)
0 7
 
< 0.1%
0.001 1
 
< 0.1%
0.002 67
0.1%
0.003 1
 
< 0.1%
0.0038 1
 
< 0.1%
ValueCountFrequency (%)
4500 1
< 0.1%
8 1
< 0.1%
0.94 1
< 0.1%
0.9 2
< 0.1%
0.6 1
< 0.1%

star_metallicity_error_max
Real number (ℝ)

Skewed 

Distinct346
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2099890275
Minimum0
Maximum4500
Zeros7
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:20:08.747870image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.05
Q10.1
median0.1
Q30.106
95-th percentile0.186
Maximum4500
Range4500
Interquartile range (IQR)0.006

Descriptive statistics

Standard deviation20.9866269
Coefficient of variation (CV)99.9415405
Kurtosis45974.23059
Mean0.2099890275
Median Absolute Deviation (MAD)0
Skewness214.4151264
Sum9654.24554
Variance440.4385086
MonotonicityNot monotonic
2025-02-19T00:20:08.826553image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1 26478
57.6%
0.08 885
 
1.9%
0.04 779
 
1.7%
0.05 762
 
1.7%
0.07 608
 
1.3%
0.06 586
 
1.3%
0.16 450
 
1.0%
0.12 402
 
0.9%
0.03 386
 
0.8%
0.15 359
 
0.8%
Other values (336) 14280
31.1%
ValueCountFrequency (%)
0 7
 
< 0.1%
0.001 1
 
< 0.1%
0.002 67
0.1%
0.003 1
 
< 0.1%
0.0038 1
 
< 0.1%
ValueCountFrequency (%)
4500 1
< 0.1%
8 1
< 0.1%
0.94 1
< 0.1%
0.9 2
< 0.1%
0.6 1
< 0.1%

star_mass_y
Real number (ℝ)

Distinct914
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.9445902939
Minimum0.011
Maximum23.47
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:20:08.900516image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.011
5-th percentile0.56
Q10.91
median0.94
Q31
95-th percentile1.25
Maximum23.47
Range23.459
Interquartile range (IQR)0.09

Descriptive statistics

Standard deviation0.2433391051
Coefficient of variation (CV)0.2576133872
Kurtosis1638.071662
Mean0.9445902939
Median Absolute Deviation (MAD)0.05
Skewness18.95665018
Sum43427.53876
Variance0.05921392008
MonotonicityNot monotonic
2025-02-19T00:20:08.986264image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.94 18262
39.7%
1.03 748
 
1.6%
0.96 659
 
1.4%
1 648
 
1.4%
0.95 630
 
1.4%
0.99 587
 
1.3%
0.93 569
 
1.2%
0.98 569
 
1.2%
0.86 551
 
1.2%
0.97 542
 
1.2%
Other values (904) 22210
48.3%
ValueCountFrequency (%)
0.011 1
< 0.1%
0.0154 1
< 0.1%
0.0162 1
< 0.1%
0.0165 1
< 0.1%
0.04 2
< 0.1%
ValueCountFrequency (%)
23.47 1
< 0.1%
9.1 1
< 0.1%
5.5 1
< 0.1%
5.23 1
< 0.1%
4.5 2
< 0.1%

star_mass_error_min
Real number (ℝ)

Skewed 

Distinct402
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0731204209
Minimum-0.269
Maximum24
Zeros11
Zeros (%)< 0.1%
Negative18
Negative (%)< 0.1%
Memory size359.3 KiB
2025-02-19T00:20:09.065512image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-0.269
5-th percentile0.028
Q10.05
median0.052
Q30.052
95-th percentile0.128
Maximum24
Range24.269
Interquartile range (IQR)0.002

Descriptive statistics

Standard deviation0.2571491322
Coefficient of variation (CV)3.516789552
Kurtosis1954.693038
Mean0.0731204209
Median Absolute Deviation (MAD)0
Skewness32.8201421
Sum3361.711351
Variance0.06612567621
MonotonicityNot monotonic
2025-02-19T00:20:09.145312image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.052 24048
52.3%
0.04 3549
 
7.7%
0.05 3150
 
6.9%
0.06 2747
 
6.0%
0.03 2042
 
4.4%
0.07 1484
 
3.2%
0.02 1072
 
2.3%
0.08 859
 
1.9%
0.09 701
 
1.5%
0.1 566
 
1.2%
Other values (392) 5757
 
12.5%
ValueCountFrequency (%)
-0.269 2
 
< 0.1%
-0.13 16
< 0.1%
0 11
< 0.1%
0.00036 1
 
< 0.1%
0.0004 1
 
< 0.1%
ValueCountFrequency (%)
24 1
 
< 0.1%
5.82 59
0.1%
3.45 1
 
< 0.1%
2.5 2
 
< 0.1%
2.18 32
0.1%

star_mass_error_max
Real number (ℝ)

Skewed 

Distinct402
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0731204209
Minimum-0.269
Maximum24
Zeros11
Zeros (%)< 0.1%
Negative18
Negative (%)< 0.1%
Memory size359.3 KiB
2025-02-19T00:20:09.208815image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-0.269
5-th percentile0.028
Q10.05
median0.052
Q30.052
95-th percentile0.128
Maximum24
Range24.269
Interquartile range (IQR)0.002

Descriptive statistics

Standard deviation0.2571491322
Coefficient of variation (CV)3.516789552
Kurtosis1954.693038
Mean0.0731204209
Median Absolute Deviation (MAD)0
Skewness32.8201421
Sum3361.711351
Variance0.06612567621
MonotonicityNot monotonic
2025-02-19T00:20:09.288813image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.052 24048
52.3%
0.04 3549
 
7.7%
0.05 3150
 
6.9%
0.06 2747
 
6.0%
0.03 2042
 
4.4%
0.07 1484
 
3.2%
0.02 1072
 
2.3%
0.08 859
 
1.9%
0.09 701
 
1.5%
0.1 566
 
1.2%
Other values (392) 5757
 
12.5%
ValueCountFrequency (%)
-0.269 2
 
< 0.1%
-0.13 16
< 0.1%
0 11
< 0.1%
0.00036 1
 
< 0.1%
0.0004 1
 
< 0.1%
ValueCountFrequency (%)
24 1
 
< 0.1%
5.82 59
0.1%
3.45 1
 
< 0.1%
2.5 2
 
< 0.1%
2.18 32
0.1%

star_radius_y
Real number (ℝ)

Skewed 

Distinct1379
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.075111179
Minimum1.43 × 10-5
Maximum91.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:20:09.344927image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1.43 × 10-5
5-th percentile0.56
Q10.88
median0.95
Q31.05
95-th percentile1.61
Maximum91.4
Range91.3999857
Interquartile range (IQR)0.17

Descriptive statistics

Standard deviation1.566112169
Coefficient of variation (CV)1.456697875
Kurtosis1468.265228
Mean1.075111179
Median Absolute Deviation (MAD)0.09
Skewness32.79883133
Sum49428.23645
Variance2.452707327
MonotonicityNot monotonic
2025-02-19T00:20:09.397943image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.95 16117
35.1%
0.89 594
 
1.3%
0.9 573
 
1.2%
0.79 527
 
1.1%
0.8 509
 
1.1%
0.94 472
 
1.0%
0.81 448
 
1.0%
0.93 441
 
1.0%
0.84 441
 
1.0%
0.86 439
 
1.0%
Other values (1369) 25414
55.3%
ValueCountFrequency (%)
1.43 × 10-53
< 0.1%
1.44 × 10-52
< 0.1%
1.87 × 10-51
 
< 0.1%
2 × 10-53
< 0.1%
0.005 1
 
< 0.1%
ValueCountFrequency (%)
91.4 3
< 0.1%
88.5 1
 
< 0.1%
86.4 1
 
< 0.1%
65.8 1
 
< 0.1%
51.1 1
 
< 0.1%

star_radius_error_min
Real number (ℝ)

Skewed 

Distinct534
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1081164238
Minimum-0.18
Maximum20.51
Zeros18
Zeros (%)< 0.1%
Negative18
Negative (%)< 0.1%
Memory size359.3 KiB
2025-02-19T00:20:09.458975image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-0.18
5-th percentile0.02
Q10.05
median0.06
Q30.1
95-th percentile0.403
Maximum20.51
Range20.69
Interquartile range (IQR)0.05

Descriptive statistics

Standard deviation0.2308182063
Coefficient of variation (CV)2.13490419
Kurtosis3091.99042
Mean0.1081164238
Median Absolute Deviation (MAD)0.02
Skewness42.86649361
Sum4970.652586
Variance0.05327704436
MonotonicityNot monotonic
2025-02-19T00:20:09.515618image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.06 15039
32.7%
0.055 3403
 
7.4%
0.02 2570
 
5.6%
0.04 2314
 
5.0%
0.03 2142
 
4.7%
0.05 1931
 
4.2%
0.07 1474
 
3.2%
0.08 971
 
2.1%
0.1 947
 
2.1%
0.01 899
 
2.0%
Other values (524) 14285
31.1%
ValueCountFrequency (%)
-0.18 16
< 0.1%
-0.06 2
 
< 0.1%
0 18
< 0.1%
9 × 10-51
 
< 0.1%
0.0001 1
 
< 0.1%
ValueCountFrequency (%)
20.51 2
< 0.1%
9.5 2
< 0.1%
9.3 1
< 0.1%
9.2 1
< 0.1%
9 2
< 0.1%

star_radius_error_max
Real number (ℝ)

Skewed 

Distinct534
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1081164238
Minimum-0.18
Maximum20.51
Zeros18
Zeros (%)< 0.1%
Negative18
Negative (%)< 0.1%
Memory size359.3 KiB
2025-02-19T00:20:09.593336image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-0.18
5-th percentile0.02
Q10.05
median0.06
Q30.1
95-th percentile0.403
Maximum20.51
Range20.69
Interquartile range (IQR)0.05

Descriptive statistics

Standard deviation0.2308182063
Coefficient of variation (CV)2.13490419
Kurtosis3091.99042
Mean0.1081164238
Median Absolute Deviation (MAD)0.02
Skewness42.86649361
Sum4970.652586
Variance0.05327704436
MonotonicityNot monotonic
2025-02-19T00:20:09.651504image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.06 15039
32.7%
0.055 3403
 
7.4%
0.02 2570
 
5.6%
0.04 2314
 
5.0%
0.03 2142
 
4.7%
0.05 1931
 
4.2%
0.07 1474
 
3.2%
0.08 971
 
2.1%
0.1 947
 
2.1%
0.01 899
 
2.0%
Other values (524) 14285
31.1%
ValueCountFrequency (%)
-0.18 16
< 0.1%
-0.06 2
 
< 0.1%
0 18
< 0.1%
9 × 10-51
 
< 0.1%
0.0001 1
 
< 0.1%
ValueCountFrequency (%)
20.51 2
< 0.1%
9.5 2
< 0.1%
9.3 1
< 0.1%
9.2 1
< 0.1%
9 2
< 0.1%

star_teff
Real number (ℝ)

Distinct2507
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5500.537706
Minimum940
Maximum42065
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:20:09.734034image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum940
5-th percentile4134
Q15419
median5574.5
Q35771
95-th percentile6200
Maximum42065
Range41125
Interquartile range (IQR)352

Descriptive statistics

Standard deviation847.4164329
Coefficient of variation (CV)0.1540606534
Kurtosis439.3031628
Mean5500.537706
Median Absolute Deviation (MAD)178.5
Skewness13.01388916
Sum252887221
Variance718114.6107
MonotonicityNot monotonic
2025-02-19T00:20:09.861243image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5574.5 13740
29.9%
5531 1808
 
3.9%
5774 146
 
0.3%
5100 142
 
0.3%
5526 141
 
0.3%
6090 117
 
0.3%
5663 116
 
0.3%
5770 110
 
0.2%
5904 107
 
0.2%
5828 103
 
0.2%
Other values (2497) 29445
64.0%
ValueCountFrequency (%)
940 1
< 0.1%
1300 1
< 0.1%
1368 1
< 0.1%
1720 1
< 0.1%
1770 1
< 0.1%
ValueCountFrequency (%)
42065 1
< 0.1%
42000 2
< 0.1%
33000 2
< 0.1%
32000 1
< 0.1%
30000 2
< 0.1%

star_teff_error_min
Real number (ℝ)

Skewed 

Distinct1756
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean111.0549879
Minimum-98.2311
Maximum15000
Zeros1
Zeros (%)< 0.1%
Negative2
Negative (%)< 0.1%
Memory size359.3 KiB
2025-02-19T00:20:09.924995image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-98.2311
5-th percentile47.72
Q189.185
median100
Q3111
95-th percentile200
Maximum15000
Range15098.2311
Interquartile range (IQR)21.815

Descriptive statistics

Standard deviation140.4689958
Coefficient of variation (CV)1.264859855
Kurtosis3970.845823
Mean111.0549879
Median Absolute Deviation (MAD)11
Skewness52.07185453
Sum5105753.068
Variance19731.53878
MonotonicityNot monotonic
2025-02-19T00:20:10.037928image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 20321
44.2%
200 2979
 
6.5%
50 533
 
1.2%
60 511
 
1.1%
122 478
 
1.0%
150 476
 
1.0%
75 390
 
0.8%
70 261
 
0.6%
90 251
 
0.5%
44 244
 
0.5%
Other values (1746) 19531
42.5%
ValueCountFrequency (%)
-98.2311 1
< 0.1%
-96.187 1
< 0.1%
0 1
< 0.1%
0.062 1
< 0.1%
0.08 2
< 0.1%
ValueCountFrequency (%)
15000 1
 
< 0.1%
10000 1
 
< 0.1%
7000 1
 
< 0.1%
5500 1
 
< 0.1%
5340 12
< 0.1%

star_teff_error_max
Real number (ℝ)

Skewed 

Distinct1756
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean111.0549879
Minimum-98.2311
Maximum15000
Zeros1
Zeros (%)< 0.1%
Negative2
Negative (%)< 0.1%
Memory size359.3 KiB
2025-02-19T00:20:10.112606image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-98.2311
5-th percentile47.72
Q189.185
median100
Q3111
95-th percentile200
Maximum15000
Range15098.2311
Interquartile range (IQR)21.815

Descriptive statistics

Standard deviation140.4689958
Coefficient of variation (CV)1.264859855
Kurtosis3970.845823
Mean111.0549879
Median Absolute Deviation (MAD)11
Skewness52.07185453
Sum5105753.068
Variance19731.53878
MonotonicityNot monotonic
2025-02-19T00:20:10.178070image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 20321
44.2%
200 2979
 
6.5%
50 533
 
1.2%
60 511
 
1.1%
122 478
 
1.0%
150 476
 
1.0%
75 390
 
0.8%
70 261
 
0.6%
90 251
 
0.5%
44 244
 
0.5%
Other values (1746) 19531
42.5%
ValueCountFrequency (%)
-98.2311 1
< 0.1%
-96.187 1
< 0.1%
0 1
< 0.1%
0.062 1
< 0.1%
0.08 2
< 0.1%
ValueCountFrequency (%)
15000 1
 
< 0.1%
10000 1
 
< 0.1%
7000 1
 
< 0.1%
5500 1
 
< 0.1%
5340 12
< 0.1%
Distinct3354
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size4.4 MiB
2025-02-19T00:20:10.383534image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length170
Median length161
Mean length42.57766177
Min length4

Characters and Unicode

Total characters1957508
Distinct characters72
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1207 ?
Unique (%)2.6%

Sample

1st rowHD 10697
2nd rowHD 107383
3rd rowunknown
4th rowunknown
5th rowunknown
ValueCountFrequency (%)
2mass 25565
 
12.7%
kic 23776
 
11.8%
wise 23697
 
11.8%
unknown 13740
 
6.8%
unkown 5065
 
2.5%
epic 1837
 
0.9%
tyc 519
 
0.3%
gsc 362
 
0.2%
hd 320
 
0.2%
268
 
0.1%
Other values (10351) 105524
52.6%
2025-02-19T00:20:10.654914image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 162947
 
8.3%
154716
 
7.9%
4 138929
 
7.1%
2 138436
 
7.1%
9 106588
 
5.4%
3 105285
 
5.4%
5 104184
 
5.3%
0 101419
 
5.2%
8 76555
 
3.9%
, 76130
 
3.9%
Other values (62) 792319
40.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1957508
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 162947
 
8.3%
154716
 
7.9%
4 138929
 
7.1%
2 138436
 
7.1%
9 106588
 
5.4%
3 105285
 
5.4%
5 104184
 
5.3%
0 101419
 
5.2%
8 76555
 
3.9%
, 76130
 
3.9%
Other values (62) 792319
40.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1957508
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 162947
 
8.3%
154716
 
7.9%
4 138929
 
7.1%
2 138436
 
7.1%
9 106588
 
5.4%
3 105285
 
5.4%
5 104184
 
5.3%
0 101419
 
5.2%
8 76555
 
3.9%
, 76130
 
3.9%
Other values (62) 792319
40.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1957508
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 162947
 
8.3%
154716
 
7.9%
4 138929
 
7.1%
2 138436
 
7.1%
9 106588
 
5.4%
3 105285
 
5.4%
5 104184
 
5.3%
0 101419
 
5.2%
8 76555
 
3.9%
, 76130
 
3.9%
Other values (62) 792319
40.5%
Distinct6815
Distinct (%)14.8%
Missing0
Missing (%)0.0%
Memory size2.9 MiB
2025-02-19T00:20:11.283524image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length25
Median length24
Mean length9.014964655
Min length3

Characters and Unicode

Total characters414463
Distinct characters65
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3149 ?
Unique (%)6.8%

Sample

1st rowunknown
2nd rowunknown
3rd rowunknown
4th rowunknown
5th rowunknown
ValueCountFrequency (%)
unknown 10769
 
22.2%
hd 1509
 
3.1%
gj 151
 
0.3%
epic 139
 
0.3%
hip 125
 
0.3%
kepler-186 75
 
0.2%
kepler-20 74
 
0.2%
kepler-62 63
 
0.1%
kepler-122 60
 
0.1%
kepler-107 59
 
0.1%
Other values (6898) 35457
73.1%
2025-02-19T00:20:12.003877image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 49146
 
11.9%
- 34199
 
8.3%
n 32356
 
7.8%
K 29956
 
7.2%
r 24629
 
5.9%
l 24557
 
5.9%
p 24510
 
5.9%
1 23877
 
5.8%
2 16238
 
3.9%
3 12682
 
3.1%
Other values (55) 142313
34.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 414463
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 49146
 
11.9%
- 34199
 
8.3%
n 32356
 
7.8%
K 29956
 
7.2%
r 24629
 
5.9%
l 24557
 
5.9%
p 24510
 
5.9%
1 23877
 
5.8%
2 16238
 
3.9%
3 12682
 
3.1%
Other values (55) 142313
34.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 414463
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 49146
 
11.9%
- 34199
 
8.3%
n 32356
 
7.8%
K 29956
 
7.2%
r 24629
 
5.9%
l 24557
 
5.9%
p 24510
 
5.9%
1 23877
 
5.8%
2 16238
 
3.9%
3 12682
 
3.1%
Other values (55) 142313
34.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 414463
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 49146
 
11.9%
- 34199
 
8.3%
n 32356
 
7.8%
K 29956
 
7.2%
r 24629
 
5.9%
l 24557
 
5.9%
p 24510
 
5.9%
1 23877
 
5.8%
2 16238
 
3.9%
3 12682
 
3.1%
Other values (55) 142313
34.3%

star_mass
Real number (ℝ)

Distinct908
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.9495335891
Minimum0.01
Maximum9.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:20:12.222655image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.59
Q10.88
median0.954
Q31.02
95-th percentile1.25
Maximum9.1
Range9.09
Interquartile range (IQR)0.14

Descriptive statistics

Standard deviation0.2154479658
Coefficient of variation (CV)0.2268987303
Kurtosis57.89752744
Mean0.9495335891
Median Absolute Deviation (MAD)0.067
Skewness1.959441361
Sum43654.80676
Variance0.04641782596
MonotonicityNot monotonic
2025-02-19T00:20:12.491673image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.954 13310
29.0%
1 661
 
1.4%
0.97 642
 
1.4%
1.04 623
 
1.4%
1.02 590
 
1.3%
0.93 589
 
1.3%
0.94 584
 
1.3%
0.95 576
 
1.3%
0.96 571
 
1.2%
1.03 551
 
1.2%
Other values (898) 27278
59.3%
ValueCountFrequency (%)
0.01 6
< 0.1%
0.011 1
 
< 0.1%
0.0165 1
 
< 0.1%
0.02 1
 
< 0.1%
0.021 1
 
< 0.1%
ValueCountFrequency (%)
9.1 1
< 0.1%
4.5 2
< 0.1%
4.3 2
< 0.1%
3.9 1
< 0.1%
3.09 2
< 0.1%

star_radius
Real number (ℝ)

Skewed 

Distinct1305
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.068708795
Minimum1.4 × 10-5
Maximum86.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:20:12.728025image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1.4 × 10-5
5-th percentile0.582
Q10.85
median0.945
Q31.07
95-th percentile1.59
Maximum86.4
Range86.399986
Interquartile range (IQR)0.22

Descriptive statistics

Standard deviation1.344179656
Coefficient of variation (CV)1.25776045
Kurtosis1401.315294
Mean1.068708795
Median Absolute Deviation (MAD)0.108
Skewness30.83513657
Sum49133.88686
Variance1.806818946
MonotonicityNot monotonic
2025-02-19T00:20:13.009542image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.945 11816
 
25.7%
0.9 507
 
1.1%
0.89 500
 
1.1%
0.93 488
 
1.1%
0.84 440
 
1.0%
0.85 418
 
0.9%
0.94 407
 
0.9%
0.91 402
 
0.9%
0.82 402
 
0.9%
0.83 382
 
0.8%
Other values (1295) 30213
65.7%
ValueCountFrequency (%)
1.4 × 10-54
< 0.1%
0.01 2
< 0.1%
0.089 1
 
< 0.1%
0.1 1
 
< 0.1%
0.107 2
< 0.1%
ValueCountFrequency (%)
86.4 1
< 0.1%
83.8 2
< 0.1%
51.1 1
< 0.1%
50.39 2
< 0.1%
50.3 1
< 0.1%

star_temperature_y
Real number (ℝ)

Distinct2473
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5529.9982
Minimum58.37
Maximum29300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:20:13.260644image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum58.37
5-th percentile4255
Q15359
median5645
Q35837
95-th percentile6231
Maximum29300
Range29241.63
Interquartile range (IQR)478

Descriptive statistics

Standard deviation664.1954914
Coefficient of variation (CV)0.1201077229
Kurtosis178.2858955
Mean5529.9982
Median Absolute Deviation (MAD)225
Skewness4.325172681
Sum254241667.2
Variance441155.6508
MonotonicityNot monotonic
2025-02-19T00:20:13.496689image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5645 12085
 
26.3%
6090 159
 
0.3%
5526 144
 
0.3%
5100 141
 
0.3%
5770 125
 
0.3%
5884 103
 
0.2%
6150 103
 
0.2%
6050 102
 
0.2%
6012 100
 
0.2%
5774 98
 
0.2%
Other values (2463) 32815
71.4%
ValueCountFrequency (%)
58.37 3
< 0.1%
58.65 1
 
< 0.1%
333 2
< 0.1%
415 1
 
< 0.1%
540 1
 
< 0.1%
ValueCountFrequency (%)
29300 1
 
< 0.1%
27730 2
< 0.1%
27500 3
< 0.1%
21700 1
 
< 0.1%
11327 1
 
< 0.1%

star_metallicity_y
Real number (ℝ)

Zeros 

Distinct353
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.004429842308
Minimum-2.09
Maximum7.79
Zeros25176
Zeros (%)54.8%
Negative8904
Negative (%)19.4%
Memory size359.3 KiB
2025-02-19T00:20:13.704500image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-2.09
5-th percentile-0.17
Q10
median0
Q30.01
95-th percentile0.21
Maximum7.79
Range9.88
Interquartile range (IQR)0.01

Descriptive statistics

Standard deviation0.1326263967
Coefficient of variation (CV)29.93930428
Kurtosis783.8738068
Mean0.004429842308
Median Absolute Deviation (MAD)0
Skewness12.27886841
Sum203.6620001
Variance0.01758976111
MonotonicityNot monotonic
2025-02-19T00:20:14.115619image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 25176
54.8%
0.04 1026
 
2.2%
0.03 1018
 
2.2%
0.02 1013
 
2.2%
0.01 957
 
2.1%
-0.03 832
 
1.8%
-0.01 778
 
1.7%
-0.02 743
 
1.6%
0.05 739
 
1.6%
0.06 642
 
1.4%
Other values (343) 13051
28.4%
ValueCountFrequency (%)
-2.09 1
< 0.1%
-1.9 2
< 0.1%
-1.84 1
< 0.1%
-1.54 1
< 0.1%
-1.46 1
< 0.1%
ValueCountFrequency (%)
7.79 3
< 0.1%
0.56 3
< 0.1%
0.522 2
< 0.1%
0.52 4
< 0.1%
0.514 1
 
< 0.1%

planet_radius
Real number (ℝ)

Distinct2165
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2879599848
Minimum0.0023
Maximum10.55143
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:20:14.340206image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.0023
5-th percentile0.097
Q10.15857
median0.203
Q30.241
95-th percentile1.08
Maximum10.55143
Range10.54913
Interquartile range (IQR)0.08243

Descriptive statistics

Standard deviation0.3538726254
Coefficient of variation (CV)1.228895138
Kurtosis96.30438946
Mean0.2879599848
Median Absolute Deviation (MAD)0.041
Skewness7.013799735
Sum13238.9603
Variance0.125225835
MonotonicityNot monotonic
2025-02-19T00:20:14.540821image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.203 13005
28.3%
0.211 174
 
0.4%
0.136 169
 
0.4%
0.178 166
 
0.4%
0.20049 141
 
0.3%
0.153 136
 
0.3%
0.128 132
 
0.3%
0.14945 129
 
0.3%
0.17 129
 
0.3%
0.112 129
 
0.3%
Other values (2155) 31665
68.9%
ValueCountFrequency (%)
0.0023 1
 
< 0.1%
0.0164379 1
 
< 0.1%
0.02187 1
 
< 0.1%
0.027 13
< 0.1%
0.02773 1
 
< 0.1%
ValueCountFrequency (%)
10.55143 1
< 0.1%
9.58873 1
< 0.1%
8.23636 1
< 0.1%
8.1106 1
< 0.1%
7.65494 1
< 0.1%

planet_temperature
Real number (ℝ)

Distinct2212
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean791.0702275
Minimum93.8
Maximum7112
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:20:14.756758image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum93.8
5-th percentile525
Q1762
median762
Q3762
95-th percentile1189
Maximum7112
Range7018.2
Interquartile range (IQR)0

Descriptive statistics

Standard deviation234.7885923
Coefficient of variation (CV)0.2967986712
Kurtosis56.4542615
Mean791.0702275
Median Absolute Deviation (MAD)0
Skewness4.574974475
Sum36369453.71
Variance55125.68309
MonotonicityNot monotonic
2025-02-19T00:20:14.991459image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
762 36124
78.6%
584 34
 
0.1%
644 30
 
0.1%
760 30
 
0.1%
660 29
 
0.1%
380 28
 
0.1%
391 27
 
0.1%
1143 26
 
0.1%
643 26
 
0.1%
910 25
 
0.1%
Other values (2202) 9596
 
20.9%
ValueCountFrequency (%)
93.8 1
 
< 0.1%
96.4 1
 
< 0.1%
102.2 1
 
< 0.1%
107.3 3
< 0.1%
117.2 2
< 0.1%
ValueCountFrequency (%)
7112 1
< 0.1%
6319.1 1
< 0.1%
6248 2
< 0.1%
6007 1
< 0.1%
4859 1
< 0.1%

planet_period
Real number (ℝ)

Skewed 

Distinct8710
Distinct (%)18.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean287.9896436
Minimum0.065115
Maximum8040000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:20:15.182717image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.065115
5-th percentile1.91694425
Q16.057342
median11.12102413
Q318.92536137
95-th percentile136.205626
Maximum8040000
Range8039999.935
Interquartile range (IQR)12.86801937

Descriptive statistics

Standard deviation37553.95296
Coefficient of variation (CV)130.4003591
Kurtosis45693.62057
Mean287.9896436
Median Absolute Deviation (MAD)5.64359113
Skewness213.4424967
Sum13240323.87
Variance1410299383
MonotonicityNot monotonic
2025-02-19T00:20:15.462106image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11.12102413 10769
 
23.4%
11.8705247 565
 
1.2%
0.8374907 23
 
0.1%
3.52474859 22
 
< 0.1%
45.294301 20
 
< 0.1%
39.792187 19
 
< 0.1%
45.154 18
 
< 0.1%
3.07222 18
 
< 0.1%
4.72673978 18
 
< 0.1%
4.4379637 18
 
< 0.1%
Other values (8700) 34485
75.0%
ValueCountFrequency (%)
0.065115 1
< 0.1%
0.090706293 1
< 0.1%
0.1768913 1
< 0.1%
0.179715 1
< 0.1%
0.2197 1
< 0.1%
ValueCountFrequency (%)
8040000 1
 
< 0.1%
166510 4
< 0.1%
104100 1
 
< 0.1%
90553.02 1
 
< 0.1%
83255 4
< 0.1%

semi_major_axis
Real number (ℝ)

Skewed 

Distinct3135
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6174526623
Minimum0.00442
Maximum6471
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:20:15.724208image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.00442
5-th percentile0.0418
Q10.104541
median0.104541
Q30.104541
95-th percentile0.4249968
Maximum6471
Range6470.99558
Interquartile range (IQR)0

Descriptive statistics

Standard deviation37.95562534
Coefficient of variation (CV)61.47131215
Kurtosis20742.83494
Mean0.6174526623
Median Absolute Deviation (MAD)0
Skewness136.2717307
Sum28387.38615
Variance1440.629495
MonotonicityNot monotonic
2025-02-19T00:20:15.974055image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.104541 32691
71.1%
0.052 85
 
0.2%
0.08 63
 
0.1%
0.047 57
 
0.1%
0.067 52
 
0.1%
0.053 49
 
0.1%
0.055 48
 
0.1%
0.059 48
 
0.1%
0.11 45
 
0.1%
0.04 45
 
0.1%
Other values (3125) 12792
 
27.8%
ValueCountFrequency (%)
0.00442 1
< 0.1%
0.0048 1
< 0.1%
0.005 1
< 0.1%
0.0058 1
< 0.1%
0.006 2
< 0.1%
ValueCountFrequency (%)
6471 1
< 0.1%
3500 1
< 0.1%
2880 1
< 0.1%
1662 1
< 0.1%
487.1 2
< 0.1%
Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.8 MiB
2025-02-19T00:20:16.204863image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length15
Median length7
Mean length6.855638934
Min length2

Characters and Unicode

Total characters315188
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowunknown
2nd rowunknown
3rd rowunknown
4th rowunknown
5th rowunknown
ValueCountFrequency (%)
transit 28975
63.0%
unknown 14618
31.8%
rv 1775
 
3.9%
microlensing 451
 
1.0%
imaging 108
 
0.2%
timing 44
 
0.1%
disk 3
 
< 0.1%
kinematics 3
 
< 0.1%
astrometry 1
 
< 0.1%
2025-02-19T00:20:16.580572image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 73886
23.4%
t 57999
18.4%
i 30190
9.6%
s 29433
 
9.3%
r 29428
 
9.3%
a 29087
 
9.2%
o 15070
 
4.8%
k 14624
 
4.6%
u 14618
 
4.6%
w 14618
 
4.6%
Other values (10) 6235
 
2.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 315188
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 73886
23.4%
t 57999
18.4%
i 30190
9.6%
s 29433
 
9.3%
r 29428
 
9.3%
a 29087
 
9.2%
o 15070
 
4.8%
k 14624
 
4.6%
u 14618
 
4.6%
w 14618
 
4.6%
Other values (10) 6235
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 315188
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 73886
23.4%
t 57999
18.4%
i 30190
9.6%
s 29433
 
9.3%
r 29428
 
9.3%
a 29087
 
9.2%
o 15070
 
4.8%
k 14624
 
4.6%
u 14618
 
4.6%
w 14618
 
4.6%
Other values (10) 6235
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 315188
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 73886
23.4%
t 57999
18.4%
i 30190
9.6%
s 29433
 
9.3%
r 29428
 
9.3%
a 29087
 
9.2%
o 15070
 
4.8%
k 14624
 
4.6%
u 14618
 
4.6%
w 14618
 
4.6%
Other values (10) 6235
 
2.0%

is_transiting
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.9500598151
Minimum0
Maximum1
Zeros2296
Zeros (%)5.0%
Negative0
Negative (%)0.0%
Memory size359.3 KiB
2025-02-19T00:20:16.721452image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2178237701
Coefficient of variation (CV)0.2292737433
Kurtosis15.0782903
Mean0.9500598151
Median Absolute Deviation (MAD)0
Skewness-4.132509451
Sum43679
Variance0.04744719484
MonotonicityNot monotonic
2025-02-19T00:20:16.817093image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
1 43679
95.0%
0 2296
 
5.0%
ValueCountFrequency (%)
0 2296
 
5.0%
1 43679
95.0%
ValueCountFrequency (%)
1 43679
95.0%
0 2296
 
5.0%